Revisiting Hansen Solubility Parameters by Including Thermodynamics

Abstract

The Hansen solubility parameter approach is revisited by implementing the thermodynamics of dissolution and mixing. Hansen's pragmatic approach has earned its spurs in predicting solvents for polymer solutions, but for molecular solutes improvements are needed. By going into the details of entropy and enthalpy, several corrections are suggested that make the methodology thermodynamically sound without losing its ease of use. The most important corrections include accounting for the solvent molecules’ size, the destruction of the solid's crystal structure, and the specificity of hydrogen‐bonding interactions, as well as opportunities to predict the solubility at extrapolated temperatures. Testing the original and the improved methods on a large industrial dataset including solvent blends, fit qualities improved from 0.89 to 0.97 and the percentage of correct predictions rose from 54 % to 78 %. Full Matlab scripts are included in the Supporting Information, allowing readers to implement these improvements on their own datasets.

A Novel Rheological Method to Assess Drug-Polymer Interactions Regarding Miscibility and Crystallization of Drug in Amorphous Solid Dispersions for Oral Drug Delivery

“…An application to high-energy solids like amorphous compounds [76] can be viewed similar to a supercooled liquid, but it is only an approximation [36]. In addition, it has been highlighted that the HSP calculations lack more detailed thermodynamic and, specifically, entropic considerations [36][37][38]. It is interesting to mention in the context of entropy, that the prediction of solubility in solvents via the original experimental Hansen method [58] seems to be more accurate for larger molecules, such as in paints and polymer mixtures [37] than using it for small-molecular APIs [77] in pharmaceutics and cosmetics [78].…”

“…More promising is here the use of partial solubility parameters (e.g., the Hansen solubility parameters) to differentiate between dispersive, polar, and hydrogen bonding interactions [36]. There are still several theoretical limitations reported, which can be viewed as a downside of the given simplicity [37,38]. Partial solubility parameters are still useful, especially when they are predicted in silico, as the otherwise experimental determination is quite time consuming and often not practical in early formulation development [39].…”

Increasing the Prediction Efficiency of Hansen Solubility Parameters in Supercritical Fluids

“…The proposed modifications are not sufficient to accurately predict the behavior of solute-solvent interactions. Therefore it is important for small solute molecules to reconsider the classic calculation of HSPs by the group contribution method, using the newly developed correction, based on thermodynamical considerations, by Louwerse and collaborators [27]. The basis for this is the presumption that when a molecule leaves the crystal structure or its own neighborhood, by dissolving in another environment, the process evolves with an entropy growth and an enthalpy loss, while a negative ΔG is maintained.…”

Application of Multivariate Adaptive Regression Splines (MARSplines) for Predicting Hansen Solubility Parameters Based on 1D and 2D Molecular Descriptors Computed from SMILES String

“…By calculating the Euclidean distance between two points in the Hansen space, one can evaluate the miscibility of two substances according to the commonly known rule "similia similibus solvuntur." ere are many scientific and industrial fields of Hansen solubility parameters application, including polymer materials, paints, and coatings (e.g., miscibility and solubility [5][6][7][8][9], environmental stress cracking [10,11], adhesion [12], plasticizers compatibility [13], swelling, solvent diffusion, and permeation [14,15], and polymer sensors designing [16], pigments and nanomaterials dispersibility [3,[17][18][19][20]), membrane filtration techniques [21], and pharmaceutics and pharmaceutical technology (e.g., solubility [22][23][24][25][26][27], cocrystal screening [28,29], drug-DNA interaction [30], drug's absorption site prediction [31], skin permeation [32], drug-nail affinity [33], drug-polymer miscibility, and hot-melt extrusion technology [34][35][36][37]).…”