Thermodynamic analysis of the solubility and preferential solvation of sulfamerazine in (acetonitrile + water) cosolvent mixtures at different temperatures

Blanco-Márquez, Joaquín H.; Ortíz, Claudia Patricia; Cerquera, Néstor Enrique; Martínez, Fleming; Jouyban, Abolghasem; Delgado, Daniel Ricardo

doi:10.1016/j.molliq.2019.111507

Cited by 24 publications

(11 citation statements)

References 43 publications

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“…The procedure was the same as that developed and published by this research group in previous research [18]. The quantification of the solubility of SMT in the MeCN + MeOH co-solvent mixtures was carried out according to the flask shaking method proposed by Higuchi and Connors [19].…”

Section: Solubility Determinationmentioning

confidence: 99%

Solubility of Sulfamethazine in the Binary Mixture of Acetonitrile + Methanol from 278.15 to 318.15 K: Measurement, Dissolution Thermodynamics, Preferential Solvation, and Correlation

et al. 2021

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Solubility of sulfamethazine (SMT) in acetonitrile (MeCN) + methanol (MeOH) cosolvents was determined at nine temperatures between 278.15 and 318.15 K. From the solubility data expressed in molar fraction, the thermodynamic functions of solution, transfer and mixing were calculated using the Gibbs and van ’t Hoff equations; on the other hand, the solubility data were modeled according to the Wilson models and NRTL. The solubility of SMT is thermo-dependent and is influenced by the solubility parameter of the cosolvent mixtures. In this case, the maximum solubility was achieved in the cosolvent mixture w0.40 at 318.15 K and the minimum in pure MeOH at 278.15 K. According to the thermodynamic functions, the SMT solution process is endothermic in addition to being favored by the entropic factor, and as for the preferential solvation parameter, SMT tends to be preferentially solvated by MeOH in all cosolvent systems; however, δx3,1<0.01, so the results are not conclusive. Finally, according to mean relative deviations (MRD%), the two models could be very useful tools for calculating the solubility of SMT in cosolvent mixtures and temperatures different from those reported in this research.

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Section: Solubility Determinationmentioning

confidence: 99%

Solubility of Sulfamethazine in the Binary Mixture of Acetonitrile + Methanol from 278.15 to 318.15 K: Measurement, Dissolution Thermodynamics, Preferential Solvation, and Correlation

et al. 2021

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“…Among the most often utilized are micronization [ 17 ], monocrystal formation [ 18 , 19 ], amorphization [ 20 , 21 , 22 ], complexation with cyclodextrins [ 23 , 24 ], solid dispersion formation [ 25 ], pH modification [ 26 , 27 ], formation of salts [ 28 , 29 ] and cocrystals [ 30 , 31 ]. The usage of hydrotropes or cosolvation techniques also offers an interesting and relatively simple way of enhancing solubility [ 32 , 33 ]. The cosolvation effect takes place when a particular amount of a cosolvent is added to the primary solvent and causes a solubility increase [ 34 ].…”

Section: Introductionmentioning

confidence: 99%

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

Cysewski

Jeliński

Cymerman

et al. 2021

IJMS

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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.

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“…Many approaches have been proposed to address this challenge, including micronization [ 27 ], monocrystal formation [ 28 , 29 ], amorphization [ 30 , 31 , 32 ], complexation with cyclodextrins [ 33 , 34 ], solid dispersion formation [ 35 ], pH modification [ 36 , 37 ], formation of salts [ 38 , 39 ] and cocrystals [ 40 , 41 , 42 , 43 ]. A very promising and simple way of increasing solubility is the usage of cosolvation techniques [ 44 , 45 ]. The cosolvation effect is achieved when an addition of some amount of a particular solvent to the primary solvent results in increased solubility of the solute [ 46 ].…”

Section: Introductionmentioning

confidence: 99%

Experimental and Theoretical Study on Theobromine Solubility Enhancement in Binary Aqueous Solutions and Ternary Designed Solvents

et al. 2021

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The solubility of theobromine was studied both experimentally and theoretically. The solubility was determined spectrophotometrically at 25 °C in neat organic solvents, aqueous binary mixtures, Natural Deep Eutectic Solvents (NADES) and ternary NADES mixtures with water. It was found that addition of water in unimolar proportions with some organic solvents increases theobromine solubility compared to neat solvents. Additionally, using NADES results in a solubility increase of the studied compound not only in relation to water but also DMSO. The addition of water (0.2 molar fraction) to NADES is responsible for an even larger increase of solubility. The measured solubilities were interpreted in terms of three theoretical frameworks. The first one—belonging to the set of data reduction techniques—proved to be very efficient in quantitative back-computations of excess solubility of theobromine in all studied systems. The default approach utilizing the well-recognized COSMO-RS (Conductor-like Screening Model for Real Solvents) framework offered at most a qualitative solubility description. The extended search for possible contacts provided evidence for the existence of many intermolecular complexes that alter the electron density of the solute molecule, thus influencing solubility computations. Taking into account such intermolecular contacts by using the COSMO-RS-DARE (Conductor-like Screening Model for Realistic Solvation-Dimerization, Aggregation, and Reaction Extension) framework seriously increased the accuracy of solubility computations.

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Thermodynamic analysis of the solubility and preferential solvation of sulfamerazine in (acetonitrile + water) cosolvent mixtures at different temperatures

Cited by 24 publications

References 43 publications

Solubility of Sulfamethazine in the Binary Mixture of Acetonitrile + Methanol from 278.15 to 318.15 K: Measurement, Dissolution Thermodynamics, Preferential Solvation, and Correlation

Solubility of Sulfamethazine in the Binary Mixture of Acetonitrile + Methanol from 278.15 to 318.15 K: Measurement, Dissolution Thermodynamics, Preferential Solvation, and Correlation

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

Experimental and Theoretical Study on Theobromine Solubility Enhancement in Binary Aqueous Solutions and Ternary Designed Solvents

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