Abstract
Purpose
Pharmaceutical gelatin shell capsules are commonly used to deliver powdered solid dosage forms. The dissolution behavior of these products depends on a number of factors, including, notably, powder distribution within capsules. Powder agglomeration occurring during the filling and sealing stages may lead to regulatory compliance issues. Although not a typical procedure, X-ray images of the final capsules may be inspected manually to determine the presence of such agglomerates.
Methods
The objective of this study was to develop a screening system, based on X-ray image analysis, capable of distinguishing capsules containing agglomerated powder from those containing unagglomerated powder. To do so, capsules were produced under various conditions to induce differing levels of agglomeration. Samples were first classed according to expert opinion before being tested to calibrate chemometric soft independent modeling by class analogy. As capsules were cylindrical and visually opaque, each was imaged multiple times to determine the robustness of the method to uneven powder agglomeration inside the capsules.
Results and Conclusions
The results show that X-ray imaging can automatically detect and classify powder agglomerates within pharmaceutical capsules, thus reducing reliance on subjective human inspection while increasing the online potential of capsule imaging.
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Acknowledgments
The authors are indebted to Pfizer Inc., the Natural Sciences and Engineering Council of Canada, and the Université de Sherbrooke for financial support. Technical assistance from George Sienkiewicz, Amanda Carr, and Jordan Cheyne at Pfizer is gratefully acknowledged.
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Gosselin, R., Vachon Lachance, E., Cournoyer, A. et al. Classifying Pharmaceutical Capsules Through X-Ray Image Analysis Based on the Agglomeration of Their Contents. J Pharm Innov 11, 92–101 (2016). https://doi.org/10.1007/s12247-015-9241-6
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DOI: https://doi.org/10.1007/s12247-015-9241-6