DISSOLUTION PROFILE SIMILARITY ANALYSES-STATISTICAL PRINCIPLES, METHODS AND CONSIDERATIONS.

Autor: Hoffelder T; Global Biostatistics and Data Sciences, Boehringer Ingelheim Pharma GmbH & Co. KG, Binger Straße 173, 55216, Ingelheim Am Rhein, Germany. thomas.hoffelder@boehringer-ingelheim.com., Leblond D; Consultant in CMC Statistical Studies, 3091 Midlane Drive, Wadsworth, IL, 60083, United States of America., Van Alstine L; Pfizer Inc, Eastern Point Road, Groton, Connecticut, 06340, United States of America., Diaz DA; Pfizer Inc, Eastern Point Road, Groton, Connecticut, 06340, United States of America., Suarez-Sharp S; Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, Maryland, United States of America.; Regulatory Affairs, Simulations Plus Inc, 42505 10th Street West, Lancaster, CA, 93534, United States of America., Witkowski K; Center for Mathematical Sciences, Merck Manufacturing Division, Merck & Co., Inc, Kenilworth, NJ, 07033, United States of America., Altan S; Statistics and Decision Sciences, Manufacturing and Applied Statistics, Janssen Pharmaceutical R&D LLD, Raritan, NJ, 08869, United States of America., Reynolds J; Data and Statistical Sciences, AbbVie Inc, North Chicago, IL, 60064, United States of America., Bergeron Z; Agios Pharmaceuticals, 88 Sidney St., Cambridge, MA, 02143, United States of America.; Sage Therapeutics, 215 First St, Cambridge, MA, 02142, United States of America., Lief K; CMC Statistics, Biostatistics, GlaxoSmithKline, David Jack Centre for R&D, Ware, SG12 0DP, Hertfordshire, UK., Zheng Y; Data and Statistical Sciences, AbbVie Inc, North Chicago, IL, 60064, United States of America., Abend A; Pharmaceutical Sciences, Merck & Co., Inc., 770 Sumneytown Pike, West Point, PA, 19486, United States of America.
Jazyk: angličtina
Zdroj: The AAPS journal [AAPS J] 2022 Apr 06; Vol. 24 (3), pp. 54. Date of Electronic Publication: 2022 Apr 06.
DOI: 10.1208/s12248-022-00697-y
Abstrakt: The pharmaceutical industry and regulatory agencies rely on dissolution similarity testing to make critical product 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 with the emphasis given to the similarity factor f 2 with little discussion of alternative methods. In an effort to highlight current practices to assess dissolution profile similarity and to strive toward global harmonization, a workshop entitled "In Vitro Dissolution Similarity Assessment in Support of Drug Product Quality: What, How, When" was held on May 21-22, 2019 at the University of Maryland, Baltimore. This manuscript provides in-depth discussion of the mathematical principles of the model-independent statistical methods for dissolution profile similarity analyses presented in the workshop. Deeper understanding of the testing objective and statistical properties of the available statistical methods is essential to identify methods which are appropriate for application in practice. A decision tree is provided to aid in the selection of an appropriate statistical method based on the underlying characteristics of the drug product. Finally, the design of dissolution profile studies is addressed regarding analytical and statistical recommendations to sufficiently power the study. This includes a detailed discussion on evaluation of dissolution profile data for which several batches per reference and/or test product are available.
(© 2022. The Author(s), under exclusive licence to American Association of Pharmaceutical Scientists.)
Databáze: MEDLINE
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