Solubility Study of Acetylsalicylic Acid in Ethanol + Water Mixtures: Measurement, Mathematical Modeling, and Stability Discussion

Solubility determination of poorly water-soluble drugs is pivotal for formulation scientists when they want to develop a liquid formulation. Performing such a test with different ratios of cosolvents with water is time-consuming and costly. The scarcity of solubility data for poorly water-soluble drugs increases the importance of developing correlation and prediction equations for these mixtures. Therefore, the aim of the current research is to determine the solubility of acetylsalicylic acid in binary mixtures of ethanol+water at 25 and 37°C. Acetylsalicylic acid is non-stable in aqueous solutions and readily hydrolyze to salicylic acid. So, the solubility of acetylsalicylic acid is measured in ethanolic mixtures by HPLC to follow the concentration of produced salicylic acid as well. Moreover, the solubility of acetylsalicylic acid is modeled using different cosolvency equations. The measured solubility data were also predicted using PC-SAFT EOS model. DSC results ruled out any changes in the polymorphic form of acetylsalicylic acid after the solubility test, whereas XRPD results showed some changes in crystallinity of the precipitated acetylsalicylic acid after the solubility test. Fitting the solubility data to the different cosolvency models showed that the mean relative deviation percentage for the Jouyban-Acree model was less than 10.0% showing that this equation is able to obtain accurate solubility data for acetylsalicylic acid in mixtures of ethanol and water. Also, the predicted data with an average mean relative deviation percentage (MRD%) of less than 29.65% show the capability of the PC-SAFT model for predicting solubility data. A brief comparison of the solubilities of structurally related solutes to acetylsalicylic acid was also provided.

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 (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.

Solubility of Hybrid Halide Perovskites in DMF and DMSO

Solution methods remain the most popular means for the fabrication of hybrid halide perovskites. However, the solubility of hybrid perovskites has not yet been quantitively investigated. In this study, we present accurate solubility data for MAPbI3, FAPbI3, MAPbBr3 and FAPbBr3 in the two most widely used solvents, DMF and DMSO, and demonstrate huge differences in the solubility behavior depending on the solution compositions. By analyzing the donor numbers of the solvents and halide anions, we rationalize the differences in the solubility behavior of hybrid perovskites with various compositions, in order to take a step forward in the search for better processing conditions of hybrid perovskites for solar cells and optoelectronics.

Prediction of small-molecule compound solubility in organic solvents by machine learning algorithms

Rapid solvent selection is of great significance in chemistry. However, solubility prediction remains a crucial challenge. This study aimed to develop machine learning models that can accurately predict compound solubility in organic solvents. A dataset containing 5081 experimental temperature and solubility data of compounds in organic solvents was extracted and standardized. Molecular fingerprints were selected to characterize structural features. lightGBM was compared with deep learning and traditional machine learning (PLS, Ridge regression, kNN, DT, ET, RF, SVM) to develop models for predicting solubility in organic solvents at different temperatures. Compared to other models, lightGBM exhibited significantly better overall generalization (logS ± 0.20). For unseen solutes, our model gave a prediction accuracy (logS ± 0.59) close to the expected noise level of experimental solubility data. lightGBM revealed the physicochemical relationship between solubility and structural features. Our method enables rapid solvent screening in chemistry and may be applied to solubility prediction in other solvents.

Solutions, in Particular Dilute Solutions of Nonelectrolytes: A Review

The liquid state is one of the three principal states of matter and arguably the most important one; and liquid mixtures represent a large research field of profound theoretical and practical interest. This topic is of importance in many areas of the applied sciences, such as in chemical engineering, geochemistry, the environmental sciences, biophysics and biomedical technology. First, I will concisely present a review of important concepts from classical thermodynamics of nonelectrolyte solutions; this will be followed by a survey of (semi-)empirical approaches to representing the composition and temperature dependence of selected thermodynamic mixture properties, and finally the focus will be on dilute binary nonelectrolyte solutions where one component, a supercritical solute, is present in much smaller quantity than the other component, called the solvent. Partial molar properties in the limit of infinite dilution (indicated by a superscript ∞) are of particular interest. For instance, activity coefficients (Lewis–Randall (LR) convention) are customarily used to characterize mixing behavior, and infinite-dilution values $$\gamma_{i}^{{{\text{LR,}}\infty }}$$ γ i LR, ∞ provide a convenient route for obtaining binary parameters for several popular solution models. When discussing solute (j)—solvent (i) interactions in solutions where the solute is supercritical, the Henry fugacity $$h_{j,i} \left( {T,P} \right)$$ h j , i T , P , also known as Henry’s law (HL) constant, is a measurable thermodynamic key quantity. Its temperature dependence yields information on the partial molar enthalpy change on solution $$\Delta H_{j}^{\infty } \left( {T,P} \right)$$ Δ H j ∞ T , P , while its pressure dependence yields information on the partial molar volume $$V_{j}^{{{\text{L,}}\infty }} \left( {T,P} \right)$$ V j L, ∞ T , P of solute j in the liquid phase (superscript L). I will clarify issues frequently overlooked, touch upon solubility data reduction and correlation, report a few recent high-precision experimental results on dilute aqueous solutions of supercritical nonelectrolytes, and show the equivalency of results for caloric quantities (e.g. $$\Delta H_{j}^{\infty }$$ Δ H j ∞ ) obtained via van ’t Hoff analysis of high-precision solubility data with directly measured calorimetric data.

Isavuconazole: Thermodynamic Evaluation of Processes Sublimation, Dissolution and Partition in Pharmaceutically Relevant Media

A temperature dependence of saturated vapor pressure of isavuconazole (IVZ), an antimycotic drug, was found by using the method of inert gas-carrier transfer and the thermodynamic functions of sublimation were calculated at a temperature of 298.15 K. The value of the compound standard molar enthalpy of sublimation was found to be 138.1 ± 0.5 kJ·mol−1. The IVZ thermophysical properties—melting point and enthalpy—equaled 302.7 K and 29.9 kJ mol−1, respectively. The isothermal saturation method was used to determine the drug solubility in seven pharmaceutically relevant solvents within the temperature range from 293.15 to 313.15 K. The IVZ solubility in the studied solvents increased in the following order: buffer pH 7.4, buffer pH 2.0, buffer pH 1.2, hexane, 1-octanol, 1-propanol, ethanol. Depending on the solvent chemical nature, the compound solubility varied from 6.7 × 10−6 to 0.3 mol·L−1. The Hansen s approach was used for evaluating and analyzing the solubility data of drug. The results show that this model well-described intermolecular interactions in the solutions studied. It was established that in comparison with the van’t Hoff model, the modified Apelblat one ensured the best correlation with the experimental solubility data of the studied drug. The activity coefficients at infinite dilution and dissolution excess thermodynamic functions of IVZ were calculated in each of the solvents. Temperature dependences of the compound partition coefficients were obtained in a binary 1-octanol/buffer pH 7.4 system and the transfer thermodynamic functions were calculated. The drug distribution from the aqueous solution to the organic medium was found to be spontaneous and entropy-driven.