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In Vitro Dissolution Profiles Similarity Assessment in Support of Drug Product Quality: What, How, When—Workshop Summary Report

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  • Theme: Current and Novel Approaches towards Dissolution Profile Comparison Harmonization
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Abstract

The pharmaceutical industry and regulatory agencies rely on dissolution similarity testing to make critical product performance decisions as part of drug product life cycle management. Accordingly, the application of mathematical approaches to evaluate dissolution profile similarity is described in regulatory guidance. However, the requirements (e.g., which time points, number of time points, %CV) to apply the widely known similarity factor f2 and other alternative statistical approaches diverge noticeably across regulatory agencies. In an effort to highlight current practices to assess dissolution profile similarity and to strive towards global harmonization, a workshop entitled “in vitro dissolution similarity assessment in support of drug product quality: what, how, when” was held May 21–22, 2019, at the University of Maryland, Baltimore. This article summarizes key points from the podium presentations and breakout (BO) sessions focusing on (1) contrasting the advantages and disadvantages of several statistical methods; (2) the importance of experimental design for successful similarity evaluation; (3) the value of similarity evaluation in light of clinically relevant specifications; and (4) the need for creating a robust and scientifically appropriate path (e.g., non-prescriptive decision tree) for dissolution profile similarity assessment as a stepping stone for global harmonization.

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Fig. 1
Figure 2

Notes

  1. In the statistical literature, the terms “group” or “population” are used when referring to “product.”

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Acknowledgments

The meeting organizers are indefinitely grateful to Dr. James Polli and Ms. Ann Anonsen for their tremendous efforts in organizing this workshop and to all speakers, facilitators, and scribes whose participation was key in having a very informative workshop.

Funding

This work was supported in part by a Center of Excellence in Regulatory Science and Innovation (CERSI) grant to the University of Maryland from the US Food and Drug Administration (Grant: U01FD005946).

Author information

Author notes

  1. Sandra Suarez-Sharp

    Present address: Regulatory affairs, Simulations Plus Inc, 42505 10th Street West, Lancaster, California, 93534, USA

Authors and Affiliations

  1. Division of Biopharmaceutics, Office of New Drug Products, Office of Pharmaceutical Quality, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, Maryland, 20993, USA

    Sandra Suarez-Sharp & Poonam Delvadia

  2. Pharmaceutical Sciences, Merck & Co Inc, 770 Sumneytown Pike, West Point, Pennsylvania, 19486, USA

    Andreas Abend

  3. Global Biostatistics and Data Sciences, Boehringer Ingelheim Pharma GmbH & Co. KG, Binger Straße 173, 55216, Ingelheim am Rhein, Germany

    Thomas Hoffelder

  4. CMC Statistical Studies, 3091 Midlane Drive, Wadsworth, Illinois, 60083, USA

    David Leblond

  5. Analytical R&D/Biopharmaceutics/Product Development and Life Cycle Management, EK Consulting 6 Reditt Crt, Richmond Hill, Ontario, L4C 7S4, Canada

    Elisabeth Kovacs

  6. Global Product Development, Pfizer Inc, Eastern Point Road, Groton, Connecticut, 06340, USA

    Dorys Argelia Diaz

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Correspondence to Dorys Argelia Diaz.

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Guest Editors: Andreas Abend, Dorys Argelia Diaz and Sandra Suarez Sharp

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Appendix

Appendix

Table III Statistical glossary of common dissolution similarity testing terms. Statistical tests refer to those used to ascertain dissolution similarity. “Similarity” refers to “dissolution similarity”
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Suarez-Sharp, S., Abend, A., Hoffelder, T. et al. In Vitro Dissolution Profiles Similarity Assessment in Support of Drug Product Quality: What, How, When—Workshop Summary Report. AAPS J 22, 74 (2020). https://doi.org/10.1208/s12248-020-00458-9

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