Prediction of paracetamol solubility in cosolvency systems at different temperatures

Solubility determination, mathematical modeling, and thermodynamic analysis of naproxen in binary solvent mixtures of (1-propanol/2-propanol) and ethylene glycol at different temperatures

This study investigates the solubility behavior of Naproxen (NAP) in binary solvent mixtures of 1-propanol (1-PrOH) and 2-propanol (2-PrOH) with ethylene glycol (EG) across a range of temperatures. The solubility of NAP was experimentally determined at five different temperatures (293.15 to 313.15 K), and the data were correlated using various thermodynamic models, including the van't Hoff, Jouyban-Acree, modified Wilson, mixture response surface, Jouyban-Acree-van't Hoff. The results demonstrated that NAP's solubility increases with temperature in both solvent systems. Notably, NAP exhibited higher solubility in mixtures with 1-PrOH compared to 2-PrOH, despite the lower polarity of 2-PrOH. This unexpected trend is attributed to the distinct molecular interactions, including hydrogen bonding, influenced by the structural differences between 1-PrOH and 2-PrOH. The X-ray diffraction analysis confirmed that no polymorphic transformation occurred in NAP during dissolution, maintaining its crystalline structure. The solubility data were well-correlated by the applied models, with overall MRDs% (mean relative deviation percentage) below 6.1.

Solubility of mesalazine in pseudo-binary mixtures of choline chloride/ethylene glycol deep eutectic solvent and water at 293.15 K to 313.15 K

Mesalazine (5-ASA) is a medication utilized to treat inflammatory bowel diseases involving ulcerative colitis and Crohn's disease. Mesalazine has fewer side effects but the low solubility and bioavailability of it is responsible for its delayed onset of action. Hence, the goal of this study is to determine the molar solubility of 5-ASA in aqueous pseudo-binary mixtures containing low toxic biocompatible choline chloride/ethylene glycol deep eutectic solvent (ChCl/EG DES) with DES mass fraction of 0.0-1.0 using a shake-flask technique at 293.2-313.2 K and approximately 85 kPa. The experimental results indicated that the solubility of 5-ASA enhanced by addition of DES mass fraction and also increasing temperature. The molarity values of 5-ASA were then modelled by some traditional cosolvency models, and regressed each model parameters. The back-computed molarity of 5-ASA using the selected cosolvency models presented a good consistency with the experimental data (lower mean percentage deviation than 5.14%). Moreover, the Gibbs and van't Hoff equations were employed to compute the thermodynamic functions of 5-ASA dissolution process in ChCl/EG DES + water from the temperature dependency of solubility data. This analysis presented an endothermic and entropy-driven process of 5-ASA dissolution in ChCl/EG DES + water. Furthermore, enthalpy-entropy compensation analysis represented non-linear enthalpy dissolution vs. Gibbs free energy compensation plots with positive and negative slopes for 5-ASA whereas the positive and negative slopes were probably due to the enhance in solvation of 5-ASA by ChCl/EG DES molecules and the solvent-structure loosing, respectively.

Exploring the Solubility Limits of Edaravone in Neat Solvents and Binary Mixtures: Experimental and Machine Learning Study

This study explores the edaravone solubility space encompassing both neat and binary dissolution media. Efforts were made to reveal the inherent concentration limits of common pure and mixed solvents. For this purpose, the published solubility data of the title drug were scrupulously inspected and cured, which made the dataset consistent and coherent. However, the lack of some important types of solvents in the collection called for an extension of the available pool of edaravone solubility data. Hence, new measurements were performed to collect edaravone solubility values in polar non-protic and diprotic media. Such an extended set of data was used in the machine learning process for tuning the parameters of regressor models and formulating the ensemble for predicting new data. In both phases, namely the model training and ensemble formulation, close attention was paid not only to minimizing the deviation of computed values from the experimental ones but also to ensuring high predictive power and accurate solubility computations for new systems. Furthermore, the environmental friendliness characteristics determined based on the common green solvent selection criteria, were included in the analysis. Our applied protocol led to the conclusion that the solubility space defined by ordinary solvents is limited, and it is unlikely to find solvents that are better suited for edaravone dissolution than those described in this manuscript. The theoretical framework presented in this study provides a precise guideline for conducting experiments, as well as saving time and resources in the pursuit of new findings.