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Amorphous solid dispersions (ASD) enhance solubility of poorly water-soluble drugs, yet predicting their physical stability remains challenging. This article reviews classical and advanced prediction methods, including API/polymer intrinsic properties (Tm/Tg ratio, LogP, glass-forming ability, polymer Tg), intermolecular interactions (Flory-Huggins parameter, solubility parameters), molecular modeling (quantum mechanics, molecular dynamics), and machine learning. These approaches help identify stable ASD formulations, streamline screening, and support pharmaceutical development of increasingly complex drug candidates.
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