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Published on: February 28, 2019
Improved group contribution parameter set for the application of solubility parameters to melt extrusion
Susann Just1, Frank Sievert, Markus Thommes
1Institute of Pharmaceutics and Biopharmaceutics, Heinrich-Heine-University, Düsseldorf, Germany.
Summary
A new group contribution method for Hansen Solubility Parameters (SP) was developed using solid drug data. This method improves predictions for amorphous solid dispersions produced via hot-melt extrusion.
Area of Science:
- Pharmaceutical Sciences
- Materials Science
- Physical Chemistry
Background:
- Hot-melt extrusion is crucial for amorphous solid solutions, increasing demand for drug solubility prediction tools.
- The Hansen Solubility Parameter (SP) approach predicts miscibility and solubility, but existing group contribution (GC) methods are derived from liquids, not solids.
- This limits their accuracy for predicting solid drug solubility in polymers.
Purpose of the Study:
- To develop a new group contribution (GC) parameter set for Hansen Solubility Parameters (SP) specifically for solid drugs.
- To enhance the predictive power of SP for amorphous solid dispersions, particularly those made by hot-melt extrusion.
- To validate the new GC parameter set against experimental solubility data and literature findings.
Main Methods:
- Developed a novel group contribution (GC) parameter set for Hansen Solubility Parameters (SP) using only published experimental SP data of solid drugs and excipients.
- Compared the predictive performance of the new GC parameter set with established methods (van Krevelen/Hoftyzer, Beerbower/Hansen, Breitkreutz, Stefanis/Panayiotou).
- Evaluated predictive power using correlation coefficients (r) for solubility experiments, melt extrudates, and casted films.
Main Results:
- The newly developed GC parameter set demonstrated superior predictive power compared to existing methods.
- Achieved high correlation coefficients for solubility experiments (r = -0.87 to -0.91).
- Showed excellent performance for literature data on melt extrudates and casted films (r = -0.78 to -0.96).
Conclusions:
- The new GC parameter set, derived from solid-state data, significantly improves the prediction of drug solubility in polymers.
- This advancement is vital for optimizing amorphous solid dispersion formulations produced via hot-melt extrusion.
- The developed method offers a more accurate and reliable tool for pharmaceutical scientists in formulation development.
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