Quantifying crystallinity of amlodipine maleate in amorphous solid dispersions produced by fluidized bed granulation using PAT tools.

One of the main concerns with formulations containing amorphous solid dispersions (ASDs) is their physical stability. Stability can be compromised if a formulation contains any residual crystallinity of an active pharmaceutical ingredient (API) that could act as seeds for further crystallisation. This study presents four methods for crystalline amlodipine maleate quantification in ASD, which were developed using one Raman and three NIR process analysers. A preliminary analysis revealed distinct differences between amorphous and non-amorphous forms of the API, both in the API alone and in the formulation. These differences laid the foundation for model development in subsequent steps. The development of four partial least squares (PLS) models proceeded through two stages, initially using a single granulation batch dataset for training, and then expanding to include three batches. Their predictability was evaluated on an additional batch dataset. Models were evaluated primarily using root mean square error of prediction (RMSEP), residual prediction deviation (RPD), and limit of detection along with other metrics. To the best of authors' knowledge, this is the first study that focuses on process monitoring of fluidized bed granulation used in preparation of ASD. The results of this study and their interpretations present novel aspects of Raman and NIR process analyser applications in combination with PLS.