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Classifying Pharmaceutical Capsules Through X-Ray Image Analysis Based on the Agglomeration of Their Contents

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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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Authors and Affiliations

  1. Department of Chemical and Biotechnological Engineering, Pfizer Industrial Research Chair, University of Sherbrooke, Sherbrooke, QC, Canada

    Ryan Gosselin & Emmanuel Vachon Lachance

  2. Process Analytical Sciences Group, Pfizer Canada, Montreal, QC, Canada

    Emmanuel Vachon Lachance & Antoine Cournoyer

  3. Process Analytical Sciences Group, Pfizer Ltd, Sandwich, UK

    Fiona Clarke

Authors
  1. Ryan Gosselin
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  2. Emmanuel Vachon Lachance
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  3. Antoine Cournoyer
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  4. Fiona Clarke
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Correspondence to Ryan Gosselin.

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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

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