Unveiling the impact of preparation methods, matrix/carrier type selection and drug loading on the supersaturation performance of amorphous solid dispersions.

Amorphous solid dispersions (ASDs) are widely recognized for their potential to enhance the solubility of poorly water-soluble drugs, with factors such as molecular mobility, intermolecular interactions, and storage conditions playing critical roles in their performance. However, the influence of preparation methods on their performance remains underexplored, especially regarding their supersaturation . To address this gap, the present study systematically investigates ASDs of ibuprofen (IBU, used as a model drug) prepared using two widely utilized techniques (solvent evaporation, SE, and melt-quench cooling, M-QC). Three different matrices/carriers (Soluplus®, SOL, povidone, PVP, and copovidone, PVPVA) were employed to evaluate the combined influence of preparation method, matrix/carrier type, and drug loading on ASD performance. Supersaturation behavior during dissolution, particularly its dependence on the Sink Index (SI), was a key focus. All ASDs showed successful amorphization, but molecular near-order structures differed based on the preparation method. ATR-FTIR spectroscopy revealed stronger molecular interactions in M-QC ASDs (compared to SE). Dissolution studies under supersaturation conditions (SI = 0.1 and SI = 0.2) highlighted significant performance differences. M-QC ASDs consistently exhibited higher in vitro AUC values under non-sink conditions compared to crystalline IBU. Conversely, SE ASDs showed improved supersaturation primarily under low SI conditions, especially with SOL at low drug loadings. The findings underscore the need for a systematic approach in developing ASDs, considering preparation method, matrix/carrier type, drug loading and dissolution study conditions collectively. These factors significantly influence dissolution behavior and supersaturation, emphasizing that they should not be independently studied but evaluated comprehensively to optimize ASD performance.