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Aqueous Polymeric Coatings for Pharmaceutical Dosage Forms

·2016·CRC Press eBooks

Abstract

Aqueous-based film coating has become routine in the pharmaceutical industry. This process eliminates the use of organic solvents and thus avoids economic, environmental, and toxicological issues related to residual solvents and solvent recovery. Aqueous-based coating, however, is complex and many variables may impact the final product and its performance. This fourth edition of Aqueous Polymeric Coatings for Pharmaceutical Dosage Forms aims to provide insight into the factors and parameters that should be considered and controlled for the successful development and commercialization of a coated product. The fourth edition has been revised and expanded to reflect the most recent scientific advancements from the literature. The contributing authors explain in detail, using illustrated examples, appropriate steps to solve and ideally avoid formulation, processing, and stability problems and to achieve an optimized dosage form. Trade names and chemical names of commercially marketed coatings are used throughout the text to help familiarize the reader with the various materials available for pharmaceutical applications. This book will be a valuable resource for anyone in the pharmaceutical industry working in the area of aqueous-based film coating.

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Metadata

Venue
CRC Press eBooks
Publisher
CRC Press
Published
2016-09-19
OpenAlex
W1606309567
Cited by
492
References
0
FWCI
4.30
Type
book
Language
en
Open access
closed

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CoChat. (2026). Citation check: Aqueous Polymeric Coatings for Pharmaceutical Dosage Forms. https://app.cochat.ai/papers/10.1201/9781315369938
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Aqueous Polymeric Coatings for Pharmaceutical Dosage Forms. (2016). CRC Press eBooks. https://doi.org/10.1201/9781315369938

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.