Optimization, thermodynamic characteristics and solubility predictions of natural deep eutectic solvents used for sulfonamide dissolution

Applications of therapeutic deep eutectic solvents (THEDESs) as antimicrobial and anticancer agents

Deep eutectic solvents (DESs) are green alternatives to ionic liquids with wide applications in organic synthesis and catalysis. DESs are characterized by being easily prepared, biodegradable, non-toxic and non-inflammable. When one or more of the DES components is active pharmaceutical ingredient (API), they are named as therapeutic deep eutectic solvents (THEDESs). THEDESs are prepared in order to improve the solubility and/or the permeability of the APIs. This review presents a brief summary of the most important THEDESs reported to date having antimicrobial and/or anticancer activities. The challenges and limitations of THEDES preparation were also discussed. The work presented here indicated the importance of THEDES as a promising drug delivery system that can overcome the bioavailability problems while retaining or enhancing the biological activity of its components.

Exploration of the Solubility Hyperspace of Selected Active Pharmaceutical Ingredients in Choline- and Betaine-Based Deep Eutectic Solvents: Machine Learning Modeling and Experimental Validation

Deep eutectic solvents (DESs) are popular green media used for various industrial, pharmaceutical, and biomedical applications. However, the possible compositions of eutectic systems are so numerous that it is impossible to study all of them experimentally. To remedy this limitation, the solubility landscape of selected active pharmaceutical ingredients (APIs) in choline chloride- and betaine-based deep eutectic solvents was explored using theoretical models based on machine learning. The available solubility data for the selected APIs, comprising a total of 8014 data points, were collected for the available neat solvents, binary solvent mixtures, and DESs. This set was augmented with new measurements for the popular sulfa drugs in dry DESs. The descriptors used in the machine learning protocol were obtained from the σ-profiles of the considered molecules computed within the COSMO-RS framework. A combination of six sets of descriptors and 36 regressors were tested. Taking into account both accuracy and generalization, it was concluded that the best regressor is nuSVR regressor-based predictive models trained using the relative intermolecular interactions and a twelve-step averaged simplification of the relative σ-profiles.

Biotransformation of ginsenoside compound K using β-glucosidase in deep eutectic solvents

Ginsenoside compound K (CK) holds significant potential for application in the pharmaceutical industry, which exhibits numerous pharmacological activity such as cardioprotective and antidiabetic. However, the difficult separation technique and limited yield of CK hinder its widespread use. The study investigated the process of converting ginsenoside CK using β-glucosidase. It aimed to determine the specific site where the enzyme binds and the most favorable arrangement of the enzyme. Molecular docking was also employed to determine the interaction between β-glucosidase and ginsenosides, indicating a strong and spontaneous contact force between them. The effectiveness of the conversion process was further improved using a "green" deep eutectic solvent (DES). A univariate experimental design was used to determine the composition of DES and the optimal hydrolysis conditions for β-glucosidase to convert ginsenoside Rb1 into ginsenoside CK. The employment of β-glucosidase enzymatic hydrolysis in the synthesis of rare ginsenoside CK applying the environmentally friendly solvent DES is not only viable and effective but also appropriate for industrial use. The characterization methods confirmed that DES did not disrupt the structure and conformation of β-glucosidase. In ChCl:EG = 2:1 (30%, v/v), pH 5.0 of DES buffer, reaction temperature 50 ℃, enzyme substrate mass ratio 1:1, after 36 h of reaction, the CK yield was 1.24 times that in acetate buffer, which can reach 86.2%. In this study, the process of using β-glucosidase enzymatic hydrolysis and producing rare ginsenoside CK in green solvent DES is feasible, efficient and suitable for industrial production and application.

Pharmaceutical applications of therapeutic deep eutectic systems (THEDES) in maximising drug delivery

The issue of poor solubility of active pharmaceutical ingredients (APIs) has been a salient area of investigation and novel drug delivery systems are being developed to improve the solubility of drugs, enhance their permeability and thereby their efficacy. Several techniques for solubilization enhancement of poorly soluble drugs are often employed at various stages of pharmaceutical drug product development. One such delivery system is the therapeutic deep eutectic system (THEDES), which showed great potential in the enhancement of solubility and permeability of drugs and ultimately augmenting their bioavailability. THEDES are made by mixing drugs with deep eutectic solvents (DESs) in a definite molar ratio by the hit and trial method. The DESs are a new class of green solvents which are non-toxic, cheap, easy to prepare, biodegradable and have multiple applications in the pharmaceutical industry. The terminologies such as ionic liquids (ILs), DES, THEDES, and therapeutic liquid eutectic systems (THELES) have been very much in use recently, and it is important to highlight the pharmaceutical applications of these unexplored reservoirs in drug solubilization enhancement, drug delivery routes, and in the management of various diseases. This review is aimed at discussing the components, formulation strategies, and routes of administration of THEDES that are used in developing the formulation. Also, the major pharmaceutical applications of THEDES in the treatment of various metabolic and non-metabolic diseases are reviewed.

Experimental and Theoretical Insights into the Intermolecular Interactions in Saturated Systems of Dapsone in Conventional and Deep Eutectic Solvents

Solubility is not only a crucial physicochemical property for laboratory practice but also provides valuable insight into the mechanism of saturated system organization, as a measure of the interplay between various intermolecular interactions. The importance of these data cannot be overstated, particularly when dealing with active pharmaceutical ingredients (APIs), such as dapsone. It is a commonly used anti-inflammatory and antimicrobial agent. However, its low solubility hampers its efficient applications. In this project, deep eutectic solvents (DESs) were used as solubilizing agents for dapsone as an alternative to traditional solvents. DESs were composed of choline chloride and one of six polyols. Additionally, water-DES mixtures were studied as a type of ternary solvents. The solubility of dapsone in these systems was determined spectrophotometrically. This study also analyzed the intermolecular interactions, not only in the studied eutectic systems, but also in a wide range of systems found in the literature, determined using the COSMO-RS framework. The intermolecular interactions were quantified as affinity values, which correspond to the Gibbs free energy of pair formation of dapsone molecules with constituents of regular solvents and choline chloride-based deep eutectic solvents. The patterns of solute-solute, solute-solvent, and solvent-solvent interactions that affect solubility were recognized using Orange data mining software (version 3.36.2). Finally, the computed affinity values were used to provide useful descriptors for machine learning purposes. The impact of intermolecular interactions on dapsone solubility in neat solvents, binary organic solvent mixtures, and deep eutectic solvents was analyzed and highlighted, underscoring the crucial role of dapsone self-association and providing valuable insights into complex solubility phenomena. Also the importance of solvent-solvent diversity was highlighted as a factor determining dapsone solubility. The Non-Linear Support Vector Regression (NuSVR) model, in conjunction with unique molecular descriptors, revealed exceptional predictive accuracy. Overall, this study underscores the potency of computed molecular characteristics and machine learning models in unraveling complex molecular interactions, thereby advancing our understanding of solubility phenomena within the scientific community.

Overview and thermodynamic modelling of deep eutectic solvents as co-solvents to enhance drug solubilities in water

The poor water solubility of active pharmaceutical ingredients (APIs) is a major challenge in the pharmaceutical industry. Co-solvents are sometimes added to enhance drug dissolution. A novel group of co-solvents, the Deep Eutectic Solvents (DES), have gained interest in the pharmaceutical field due to their good solvent power, biodegradability, sustainability, non-toxicity, and low cost. In this study, we first provide an overview of all the literature solubility studies involving a drug or API + water + DES, which can be a valuable list to some researchers. Then, we analyze these systems with focus on each individual drug/API and provide statistical information on each. A similar analysis is carried out with focus on the individual DESs. An investigation of the numeric values of the water-solubility enhancement by the different DESs for various drugs indicates that DESs are indeed effective co-solvents, with varying degrees of solubility enhancement, even up to 15-fold. This is strongly encouraging, indicating the need for further studies to find the most promising DESs for solubility enhancement. However, time-consuming and costly trial and error should be prevented by first screening, using theoretical-based or thermodynamic-based models. Based on this conclusion, the second part of the study is concerned with investigating and suggesting accurate thermodynamic approaches to tackle the phase equilibrium modeling of such systems. For this purpose, a large data bank was collected, consisting of 2009 solubility data of 25 different drugs/APIs mixed with water and 31 different DESs as co-solvents at various DES concentrations, over wide ranges of temperatures at atmospheric pressure. This data bank includes 107 DES + water + drug/API systems in total. The solubility data were then modeled according to the solid-liquid equilibrium framework, using the local composition activity coefficient models of NRTL, and UNIQUAC. The results showed acceptable behavior with respect to the experimental values and trends for all of the investigated systems, with AARD% values of 9.65 % and 14.08 % for the NRTL and UNIQUAC models, respectively. In general, the lower errors of NRTL, as well as its simpler calculation process and the requirement of fewer component parameters, suggest the priority of NRTL over UNIQUAC for use in this field.

Facile and stereospecific synthesis of diverse β-N-glycosyl sulfonamide scaffolds via palladium catalysis

Glycosylation is an important strategy to improve the druggability of lead compounds. Here, we present a palladium-catalysed stereospecific N-glycosylation of sulfonamides. This approach stands out with wide substrate scope, high functional group tolerance, and easy scalability, furnishing a broad spectrum of densely functionalized β-N-glycosyl sulfonamides with good efficiency and exceptional regio-/stereoselectivity. Diverse drug-like glycosulfonamido scaffolds have been constructed via a late-stage diversification strategy and various facile synthetic transformations of the products. Collectively, the established protocol provides a valuable tool for efficiently preparing glycosyl sulfonamides to facilitate drug discovery.

Leveraging the use of in vitro and computational methods to support the development of enabling oral drug products: An InPharma commentary

Due to the strong tendency towards poorly soluble drugs in modern development pipelines, enabling drug formulations such as amorphous solid dispersions, cyclodextrins, co-crystals and lipid-based formulations are frequently applied to solubilize or generate supersaturation in gastrointestinal fluids, thus enhancing oral drug absorption. Although many innovative in vitro and in silico tools have been introduced in recent years to aid development of enabling formulations, significant knowledge gaps still exist with respect to how best to implement them. As a result, the development strategy for enabling formulations varies considerably within the industry and many elements of empiricism remain. The InPharma network aims to advance a mechanistic, animal-free approach to the assessment of drug developability. This commentary focuses current status and next steps that will be taken in InPharma to identify and fully utilize 'best practice' in vitro and in silico tools for use in physiologically based biopharmaceutic models.

Tailoring Deep Eutectic Solvents to Provoke Solubility and Bioavailability of Naringin: Implications of a Computational Approach

Recently, the applications of deep eutectic solvents (DESs) as green and sustainable solvents for the solubilization of functional foods and phytophenols have dramatically risen concerning global issues on the utilization of organic solvents. Nevertheless, developing a suitable DES system for phytocomponents to enhance its solubility and bioavailability is complex and requires a sound experimental setup. Herein, we have attempted to develop DES encompassing the choline chloride (ChCl) along with oxalic acid (OA), l-glutamine (l-Glu), urea (U), and glycerol (Gro) at different ratios to elicit the solubility and bioavailability of naringin (NAR). Several DES systems were designed and tested for solubility, kinematic viscosity, and pH. Among these, DES-NAR encompassing ChCl/Gro in a 1:3 ratio exhibited the maximum solubility of NAR (232.56 ± 7.1 mg/mL) and neutral characteristic and thus considered suitable for NAR. Further, the conductor-like screening model for real solvents (COSMO-RS) has been employed to estimate the molecular and electrostatic interactions. DES-NAR was evaluated by polarized optical microscopy, Fourier-transform infrared (FTIR), differential scanning calorimetry (DSC), and ¹H NMR to investigate the molecular transition and interaction. Further, diffusion and permeability studies were performed, which suggest significant improvements in DES-NAR. Likewise, the pharmacokinetic studies revealed a two times increase in the oral bioavailability of NAR in a designed DES system. Thus, the work represents a systematic and efficient development of the DES system for a potential phytocomponent considering the biosafety impact, which may widen the interest in pharmaceutical and food sciences.

Intermolecular Interactions of Edaravone in Aqueous Solutions of Ethaline and Glyceline Inferred from Experiments and Quantum Chemistry Computations

Edaravone, acting as a cerebral protective agent, is administered to treat acute brain infarction. Its poor solubility is addressed here by means of optimizing the composition of the aqueous choline chloride (ChCl)-based eutectic solvents prepared with ethylene glycol (EG) or glycerol (GL) in the three different designed solvents compositions. The slurry method was used for spectroscopic solubility determination in temperatures between 298.15 K and 313.15 K. Measurements confirmed that ethaline (ETA = ChCl:EG = 1:2) and glyceline (GLE = ChCl:GL = 1:2) are very effective solvents for edaravone. The solubility at 298.15 K in the optimal compositions was found to be equal x_E = 0.158 (c_E = 302.96 mg/mL) and x_E = 0.105 (c_E = 191.06 mg/mL) for glyceline and ethaline, respectively. In addition, it was documented that wetting of neat eutectic mixtures increases edaravone solubility which is a fortunate circumstance not only from the perspective of a solubility advantage but also addresses high hygroscopicity of eutectic mixtures. The aqueous mixture with 0.6 mole fraction of the optimal composition yielded solubility values at 298.15 K equal to x_E = 0.193 (c_E = 459.69 mg/mL) and x_E = 0.145 (c_E = 344.22 mg/mL) for glyceline and ethaline, respectively. Since GLE is a pharmaceutically acceptable solvent, it is possible to consider this as a potential new liquid form of this drug with a tunable dosage. In fact, the recommended amount of edaravone administered to patients can be easily achieved using the studied systems. The observed high solubility is interpreted in terms of intermolecular interactions computed using the Conductor-like Screening Model for Real Solvents (COSMO-RS) approach and corrected for accounting of electron correlation, zero-point vibrational energy and basis set superposition errors. Extensive conformational search allowed for identifying the most probable contacts, the thermodynamic and geometric features of which were collected and discussed. It was documented that edaravone can form stable dimers stabilized via stacking interactions between five-membered heterocyclic rings. In addition, edaravone can act as a hydrogen bond acceptor with all components of the studied systems with the highest affinities to ion pairs of ETA and GLE. Finally, the linear regression model was formulated, which can accurately estimate edaravone solubility utilizing molecular descriptors obtained from COSMO-RS computations. This enables the screening of new eutectic solvents for finding greener replacers of designed solvents. The theoretical analysis of tautomeric equilibria confirmed that keto-isomer edaravone is predominant in the bulk liquid phase of all considered deep eutectic solvents (DES).

Detoxification of comfrey (Symphytum officinale L.) extract using natural deep eutectic solvent (NADES) and evaluation of its anti-inflammatory, antioxidant, and hepatoprotective properties

Comfrey (Symphytum officinale L.) contains rosmarinic acid which has different pharmacological activities, such as antioxidant and anti-inflammatory activities. However, the medicinal use of comfrey is limited by the hepatotoxic effect of lycopsamine in comfrey, which overshadows the health benefits of rosmarinic acid. Natural deep eutectic solvents (NADES) have a wide range of extraction properties, that provides a new approach to the detoxification of comfrey. In the present study, betaine-based and choline chloride-based NADES were screened for selective extraction of rosmarinic acid over lycopsamine. Ultrasonication was used in conjunction with NADES extraction. The chemical profile of the NADES extracts on antioxidant, anti-inflammatory and hepatotoxic activities were investigated using some chemical reagents. Betaine-urea (1:2 molar ratio, 50% water) obtained the highest content of rosmarinic acid and a low level of lycopsamine (1.934 and 0.018 mg/g, respectively). Betaine-urea was also shown to be more effective to extract rosmarinic acid compared to methanol-UAE under the same conditions, which gave lower rosmarinic acid and higher lycopsamine levels (0.007 and 0.031 mg/g, respectively). Betaine-urea extracts showed higher antioxidant and anti-inflammatory properties as compared with other NADES extracts, however, had lower hepatotoxic profile. This study recommends the use of betaine-urea to detroxify comfrey to open wider opportunities for the development of comfrey for medicinal use.

Natural deep eutectic solvents in phytonutrient extraction and other applications

Natural deep eutectic solvents (NaDESs) are considered a new type of green solvent with attractive application prospects in many fields because of their simple preparation, low cost, environmental friendliness, low volatility, high solvency capacity, designable structure, and easy biodegradability. Due to their biocompatibility, they are safe to use and are particularly suitable for natural product applications. In recent years, NaDESs have been used to extract phytonutrients (e.g., flavonoids, saponins, polysaccharides, alkaloids, quinones, phenolic acids, volatile oils, etc.) to improve their solubility, stability, and bioavailability. This review is intended to summarize and discuss recent progress in the field of natural products related to materials and preparation methods, physicochemical properties, enhancing extraction and separation, increasing solubility, improving stability and bioavailability, facilitating oral absorption of phytonutrients, and finally, highlighting the challenge for future work.

Application of the Solute-Solvent Intermolecular Interactions as Indicator of Caffeine Solubility in Aqueous Binary Aprotic and Proton Acceptor Solvents: Measurements and Quantum Chemistry Computations

The solubility of caffeine in aqueous binary mixtures was measured in five aprotic proton acceptor solvents (APAS) including dimethyl sulfoxide, dimethylformamide, 1,4-dioxane, acetonitrile, and acetone. The whole range of concentrations was studied in four temperatures between 25 °C and 40 °C. All systems exhibit a strong cosolvency effect resulting in non-monotonous solubility trends with changes of the mixture composition and showing the highest solubility at unimolar proportions of organic solvent and water. The observed solubility trends were interpreted based on the values of caffeine affinities toward homo- and hetero-molecular pairs formation, determined on an advanced quantum chemistry level including electron correlation and correction for vibrational zero-point energy. It was found that caffeine can act as a donor in pairs formation with all considered aprotic solvents using the hydrogen atom attached to the carbon in the imidazole ring. The computed values of Gibbs free energies of intermolecular pairs formation were further utilized for exploring the possibility of using them as potential solubility prognostics. A semi-quantitative relationship (R² = 0.78) between caffeine affinities and the measured solubility values was found, which was used for screening for new greener solvents. Based on the values of the environmental index (EI), four morpholine analogs were considered and corresponding caffeine affinities were computed. It was found that the same solute–solvent structural motif stabilizes hetero-molecular pairs suggesting their potential applicability as greener replacers of traditional aprotic proton acceptor solvents. This hypothesis was confirmed by additional caffeine solubility measurements in 4-formylmorpholine. This solvent happened to be even more efficient compared to DMSO and the obtained solubility profile follows the cosolvency pattern observed for other aprotic proton acceptor solvents.

Study and Computational Modeling of Fatty Acid Effects on Drug Solubility in Lipid-Based Systems

Lipid-based systems have many advantages in formulation of poorly water-soluble drugs but issues of a limited solvent capacity are often encountered in development. One of the possible solubilization approaches of especially basic drugs could be the addition of fatty acids to oils but currently, a systematic study is lacking. Therefore, the present work investigated apparently neutral and basic drugs in medium chain triglycerides (MCT) alone and with added either caproic acid (C6), caprylic acid (C8), capric acid (C10) or oleic acid (C18:1) at different levels (5 - 20%, w/w). A miniaturized solubility assay was used together with X-ray diffraction to analyze the residual solid and finally, solubility data were modeled using the conductor-like screening model for real solvents (COSMO-RS). Some drug bases had an MCT solubility of only a few mg/ml or less but addition of fatty acids provided in some formulations exceptional drug loading of up to about 20% (w/w). The solubility changes were in general more pronounced the shorter the chain length was and the longest oleic acid even displayed a negative effect in mixtures of celecoxib and fenofibrate. The COSMO-RS prediction accuracy was highly specific for the given compounds with root mean square errors (RMSE) ranging from an excellent 0.07 to a highest value of 1.12. The latter was obtained with the strongest model base pimozide for which a new solid form was found in some samples. In conclusion, targeting specific molecular interactions with the solute combined with mechanistic modeling provides new tools to advance lipid-based drug delivery.

Deep eutectic systems: An overview of fundamental aspects, current understanding and drug delivery applications

The deep eutectic system (DES) is a relatively new concept in the field of drug delivery science. DES is a class of eutectic mixtures comprised of two or more components, with a eutectic point far below than the melting temperature of the pure components. The strong hydrogen bonding interactions between DES constituents are responsible for significant lowering of melting point in DES. A significant number of molecules cannot reach from drug discovery phase to drug development phase because of poor biopharmaceutical attributes, such as solubility and permeability. DES can be a novel alternative to overcome these issues. In last few years DESs have been widely used in different pharmaceutical and chemical processes. However, comprehensive information regarding their drug delivery potential is not available. This review deals with fundamental aspects such as types, preparation, thermodynamics, toxicity, biodegradability and their applications in the field of drug delivery. Current challenges, future prospects and translational aspects of DES as drug delivery system have also been discussed.

Experimental and Theoretical Screening for Green Solvents Improving Sulfamethizole Solubility

Solubility enhancement of poorly soluble active pharmaceutical ingredients is of crucial importance for drug development and processing. Extensive experimental screening is limited due to the vast number of potential solvent combinations. Hence, theoretical models can offer valuable hints for guiding experiments aimed at providing solubility data. In this paper, we explore the possibility of applying quantum-chemistry-derived molecular descriptors, adequate for development of an ensemble of neural networks model (ENNM), for solubility computations of sulfamethizole (SMT) in neat and aqueous binary solvent mixtures. The machine learning procedure utilized information encoded in σ-potential profiles computed using the COSMO-RS approach. The resulting nonlinear model is accurate in backcomputing SMT solubility and allowed for extensive screening of green solvents. Since the experimental characteristics of SMT solubility are limited, the data pool was extended by new solubility measurements in water, five neat organic solvents (acetonitrile, N,N-dimethylformamide, dimethyl sulfoxide, 1,4-dioxane, and methanol), and their aqueous binary mixtures at 298.15, 303.15, 308.15, and 313.15 K. Experimentally determined order of decreasing SMT solubility in neat solvents is the following: N,N-dimethylformamide > dimethyl sulfoxide > methanol > acetonitrile > 1,4dioxane >> water, in all studied temperatures. Similar trends are observed for aqueous binary mixtures. Since N,N-dimethylformamide is not considered as a green solvent, the more acceptable replacers were searched for using the developed model. This step led to the conclusion that 4-formylmorpholine is a real alternative to N,N-dimethylformamide, fulfilling all requirements of both high dissolution potential and environmental friendliness.

Solvent Screening for Solubility Enhancement of Theophylline in Neat, Binary and Ternary NADES Solvents: New Measurements and Ensemble Machine Learning

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.

Thermodynamics and Intermolecular Interactions of Nicotinamide in Neat and Binary Solutions: Experimental Measurements and COSMO-RS Concentration Dependent Reactions Investigations

In this study, the temperature-dependent solubility of nicotinamide (niacin) was measured in six neat solvents and five aqueous-organic binary mixtures (methanol, 1,4-dioxane, acetonitrile, DMSO and DMF). It was discovered that the selected set of organic solvents offer all sorts of solvent effects, including co-solvent, synergistic, and anti-solvent features, enabling flexible tuning of niacin solubility. In addition, differential scanning calorimetry was used to characterize the fusion thermodynamics of nicotinamide. In particular, the heat capacity change upon melting was measured. The experimental data were interpreted by means of COSMO-RS-DARE (conductor-like screening model for realistic solvation-dimerization, aggregation, and reaction extension) for concentration dependent reactions. The solute-solute and solute-solvent intermolecular interactions were found to be significant in all of the studied systems, which was proven by the computed mutual affinity of the components at the saturated conditions. The values of the Gibbs free energies of pair formation were derived at an advanced level of theory (MP2), including corrections for electron correlation and zero point vibrational energy (ZPE). In all of the studied systems the self-association of nicotinamide was found to be a predominant intermolecular complex, irrespective of the temperature and composition of the binary system. The application of the COSMO-RS-DARE approach led to a perfect match between the computed and measured solubility data, by optimizing the parameter of intermolecular interactions.