Abstract
During the dissolution of amorphous solid dispersion (ASD) formulations, the gel layer that forms at the ASD/water interface strongly dictates the release of the active pharmaceutical ingredient (API) and, hence, the dissolution performance. Several studies have demonstrated that the switch of the gel layer from eroding to non-eroding behavior is API-specific and drug-load (DL)-dependent. This study systematically classifies the ASD release mechanisms and relates them to the phenomenon of the loss of release (LoR). The latter is thermodynamically explained and predicted via a modeled ternary phase diagram of API, polymer, and water, and is then used to describe the ASD/water interfacial layers (below and above the glass transition). To this end, the ternary phase behavior of the APIs, naproxen, and venetoclax with the polymer poly(vinylpyrrolidone-co-vinyl acetate) (PVPVA64) and water was modeled using the perturbed-chain statistical associating fluid theory (PC-SAFT). The glass transition was modeled using the Gordon-Taylor equation. The DL-dependent LoR was found to be caused by API crystallization or liquid-liquid phase separation (LLPS) at the ASD/water interface. If crystallization occurs, it was found that API and polymer release was impeded above a threshold DL at which the APIs crystallized directly at the ASD interface. If LLPS occurs, an API-rich phase and a polymer-rich phase are formed. Above a threshold DL, the less mobile and hydrophobic API-rich phase accumulates at the interface which prevents API release. LLPS is further influenced by the composition and glass transition temperature of the evolving phases and was investigated at 37 °C and 50 °C regarding impact of temperature of. The modeling results and LoR predictions were experimentally validated by means of dissolution experiments, microscopy, Raman spectroscopy, and size exclusion chromatography. The experimental results were found to be in very good agreement with the predicted release mechanisms deduced from the phase diagrams. Thus, this thermodynamic modeling approach represents a powerful mechanistic tool that can be applied to classify and quantitatively predict the DL-dependent LoR release mechanism of PVPVA64-based ASDs in water.