Non-destructive pipeline for analysis of crystalline solid dispersions

Area of Science:

• Pharmaceutical Sciences
• Materials Science
• Analytical Chemistry

Background:

• Advancements in pharmaceutical processing, particularly crystalline solid dispersions (CrySoDs), necessitate robust analytical techniques.
• Characterizing critical quality attributes (CQAs) like crystal size, morphology, and drug content is crucial for understanding processing impacts.
• Non-invasive methods are preferred for evaluating pharmaceutical products without destruction.

Purpose of the Study:

• To develop and validate a non-destructive analysis pipeline for characterizing modafinil CrySoDs within hydroxypropyl methylcellulose (HPMC) capsules.
• To establish a quantitative framework linking critical process parameters (CPPs) to CQAs in additive manufactured pharmaceutical products.
• To demonstrate the utility of X-ray micro-computed tomography (X-µCT) coupled with image processing for pharmaceutical quality control.

Main Methods:

• Utilized X-ray micro-computed tomography (X-µCT) for non-destructive 3D imaging of modafinil CrySoDs in HPMC capsules.
• Employed a Python-based image-processing strategy involving radial filtration, smoothing splines, and greyscale thresholding for data analysis.
• Applied heterogeneity index calculations and image segmentation techniques, specifically watershed segmentation, for CQA evaluation.

Main Results:

• Successfully isolated and characterized modafinil CrySoDs within HPMC capsules using the developed X-µCT pipeline.
• Watershed segmentation proved effective for analyzing crystal size, including fused crystallites.
• Demonstrated a quantitative link between processing and product quality attributes.

Conclusions:

• Established a generalizable, non-destructive workflow for the structural characterization of CrySoDs using X-µCT and image analysis.
• The developed method provides a quantitative framework for quality control in pharmaceutical additive manufacturing.
• This approach supports informed decisions in pharmaceutical development by connecting process parameters to critical quality attributes.