Applying Material Science Principles to Chemical Stability: Modelling Solid State Autoxidation in Mifepristone Containing Different Degrees of Crystal Disorder.

ABSTRACT

Ball-milling and harsh manufacturing processes often generate crystal disorder which have practical implications on the physical and chemical stabilities of solid drugs during subsequent storage, transport, and handling. The impact of the physical state of solid drugs, containing different degrees/levels of crystal disorder, on their autoxidative stability under storage has not been widely investigated. This study investigates the impact of differing degrees of crystal disorder on the autoxidation of Mifepristone (MFP) to develop a predictive (semi-empirical) stability model. Crystalline MFP was subjected to different durations of ambient ball milling, and the resulting disorder/ amorphous content was quantified using a partial least square (PLS) regression model based on Raman spectroscopy data. Samples of MFP milled to generate varying levels of disorder were subjected to a range of (accelerated) stability conditions, and periodically sampled to examine their recrystallization and degradation extents. Crystallinity was monitored by Raman spectroscopy, and the degradation was evaluated by liquid chromatography. The analyses of milled samples demonstrated a competition between recrystallization and degradation via autoxidation of MFP, to different extents depending on stability conditions/exposure time. The degradation kinetics were analyzed by accounting for the preceding amorphous content, and fitted with a diffusion model. An extended Arrhenius equation was used to predict the degradation of stored samples under long-term (25°C/60% RH) and accelerated (40°C/75% RH, 50°C/75% RH) stability conditions. This study highlights the utility of such a predictive stability model for identifying the autoxidative instability in non-crystalline/partially crystalline MFP, owing to the degradation of the amorphous phases. This study is particularly useful for identifying drug-product instability by leveraging the concept of material sciences.