Solubility of sulfacetamide in (ethanol + water) mixtures: Measurement, correlation, thermodynamics, preferential solvation and volumetric contribution at saturation

Uncovering the Molecular Mechanisms of Cosolvency and Predicting the Cosolvency Phenomenon by Molecular Simulations: A Case Study of Amino Acids

Cosolvency is an intriguing thermodynamic phenomenon. However, the lack of theoretical research restricts its development and its further applications. In this work, l-alanine, l-phenylalanine, and L-tryptophan were selected as model substances to investigate the mechanism of cosolvency at the molecular level. First, the dissolution behaviors of three amino acids were characterized to determine the solvent ratios at the occurrence of the cosolvency phenomenon. Furthermore, amino acid molecules undergo a shift in molecular conformation, which leads to changes in inter/intramolecular interactions. A molecular dynamics simulation method was proposed to calculate the trends of inter/intramolecular interactions, demonstrating that the maximum point of the inter/intramolecular interaction ratio exactly corresponds to the occurrence of the cosolvency. The cosolvency phenomenon of l-proline and l-threonine was predicted successfully based on this simulation method. These results are likely to provide in-depth comprehension and guidance for predicting the cosolvency phenomenon of amino-acid-like substances.

Revealing the Molecular Mechanism of Cosolvency Based on Thermodynamic Phase Diagram, Molecular Simulation, and Spectrum Analysis: The Tolbutamide Case

Cosolvency has been observed in many systems. To reveal the mechanism of cosolvency from the molecular level, the effects of molecular conformation, supramolecular clusters, and interactions on cosolvency were systematically investigated using tolbutamide as a model compound, through experimental exploration, spectral detection, and molecular simulation. The results show that, under the influence of intermolecular and intramolecular interactions, the dominant solute molecular conformations transform and the supramolecular clusters change in different solution systems, which then lead to the cosolvency phenomena.

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.

Experimental measurement - correlation of solubility and dissolution thermodynamics study of itraconazole in pure monosolvents at various temperatures

The information about the solubility and thermodynamic properties of solution is important for pharmaceutically important processes, formulation development, and further theoretical studies. In the present study, the solid-liquid equilibrium (solubility) for itraconazole (ITC) was determined experimentally in 14 monosolvents at temperatures between 293.15 K and 318.15 K under pressure of 0.1 MPa. The mole fraction solubilities were found to increase with increasing temperatures and followed inverse trend with the polarity of selected solvents. Besides, KAT-LSER analysis was performed to study the effect of solvent. The results revealed that the solute-solvent interaction (43.94%) was much higher than that of solvent-solvent interaction (16.59%). Thermodynamic based models like van't Hoff equation, modified Apelblat equation, Buchowski-Ksiazaczak equation, and polynomial empirical equation were applied to fit and correlate the experimental solubilities. Overall relative average deviation (RAD) and overall root-mean square deviation (104×RMSD) were observed to be minimum with the empirical polynomial equation and attained the values of 0.0033 and 0.0047, respectively. Furthermore, theoretical ideal solubilities, activity coefficients, and thermodynamic properties of dissolution including molar enthalpy, molar entropy, molar Gibbs free energy, and excess enthalpy were estimated. Ideal solubilities were projected considerably higher than experimental solubilities at each studied temperature. Thermodynamic properties of dissolution indicated that the dissolution was not a spontaneous process; observed to be endothermic (ΔH0soln>0) and enthalpy driven (ΔS0soln>0). Such solid-liquid equilibrium data of ITC will be of immense help in process and formulation development in pharmaceutical sciences.

Application of PC-SAFT EOS for Pharmaceuticals: Solubility, Co-Crystal, and Thermodynamic Modeling

In this study, the applicability of the perturbed chain statistical associating fluid theory (PC-SAFT) was evaluated for pharmaceutical compounds. For this purpose, the parameters of the PC-SAFT equation of state (EOS) were regressed by applying the experimental solubility data of 54 pharmaceuticals in pure solvents. The reported errors for train and test data show the suitability of the PC-SAFT EOS. The applicability of the PC-SAFT EOS was explored by its prediction accuracy for the ternary system of medicine in solvent mixtures. The model errors were 23 and 26% for two ternary systems of salicylic acid and lidocaine HCl in solvent mixtures of ethanol and water, respectively. The co-crystal formation of salicylic acid-sulfamethazine in methanol was investigated by the PC-SAFT EOS. Finally, the reaction and crystallization sections for acetaminophen production from p-aminophenol were simulated by accompanying the PC-SAFT EOS and equilibrium assumption. The purification efficiencies for acetaminophen were obtained to be 93-98% for different temperatures.