The continued advancement of processing technologies for pharmaceutical drug products via crystalline solid dispersion (CrySoD) requires non-invasive analytical methods capable of characterizing resultant products to understand the impact of processing choices on critical quality attributes (CQAs, e.g., crystal size, morphology, and drug content). In this study, we demonstrate a non-destructive and robust analysis pipeline using X-ray micro-computed tomography (X‑µCT) and a Python-based image-processing strategy to evaluate modafinil CrySoDs within hydroxypropyl methylcellulose (HPMC) capsules produced via solution-based additive manufacturing. X-µCT scans were first processed using radial filtration and smoothing splines to isolate the capsule object, and then the active pharmaceutical ingredient (modafinil) was isolated from the scans using greyscale thresholding based on X-µCT intensities. The CQAs were then evaluated using a combination of heterogeneity index calculations and image segmentation approaches. Watershed segmentation was most effective in crystal size analysis, as it can segment and separately characterize fused crystallites, which are well-dispersed in the capsules. Overall, this work establishes a generalizable, non-destructive workflow that might be used for the structural characterization of CrySoDs and provides a quantitative framework that links critical process parameters (CPPs) to final product CQAs.
Jorgensen et al. (Mon,) studied this question.