Investigation of the Influence of Copovidone Properties and Hot-Melt Extrusion Process on Level of Impurities, In Vitro Release, and Stability of an Amorphous Solid Dispersion Product.

Hot-melt extrusion (HME) is a widely used method for creating amorphous solid dispersions (ASDs) of poorly soluble drug substances, where the drug is molecularly dispersed in a solid polymer matrix. This study examines the impact of three different copovidone excipients, their reactive impurity levels, HME barrel temperature, and the distribution of colloidal silicon dioxide (SiO) on impurity levels, stability, and drug release of ASDs and their tablets. Initial peroxide levels were higher in Kollidon VA 64 (KVA64) and Plasdone S630 (PS630) compared to Plasdone S630 Ultra (PS630U), leading to greater oxidative degradation of the drug in fresh ASD tablets.

Amorphous Solid Dispersions: Implication of Method of Preparation and Physicochemical Properties of API and Excipients.

The present study investigated the effect of different polymers and manufacturing methods (hot melt extrusion, HME, and spray drying, SD) on the solid state, stability and pharmaceutical performance of amorphous solid dispersions. In the present manuscript, a combination of different binary amorphous solid dispersions containing 20% and 30% of drug loadings were prepared using SD and HME. The developed solid-state properties of the dispersions were evaluated using small- and wide-angle X-ray scattering (WAXS) and modulated differential scanning calorimetry (mDSC).

Accelerative Solid-State Oxidation Behaviour of Amorphous and Partially Crystalline Venetoclax.

There is a growing focus on solid-state degradation, especially for its relevance in understanding interactions with excipients. Performing a solid-state degradation of Venetoclax (VEN), we delve into VEN's stability in different solid-state oxidative stress conditions, utilizing Peroxydone™ complex and urea peroxide (UHP). The investigation extends beyond traditional forced degradation scenarios, providing insights into VEN's behavior over 32 h, considering temperature and crystallinity conditions.

Material to system-level benchmarking of CMOS-integrated RRAM with ultra-fast switching for low power on-chip learning.

Analog hardware-based training provides a promising solution to developing state-of-the-art power-hungry artificial intelligence models. Non-volatile memory hardware such as resistive random access memory (RRAM) has the potential to provide a low power alternative. The training accuracy of analog hardware depends on RRAM switching properties including the number of discrete conductance states and conductance variability.

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

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.