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Multivariate Analysis and Statistics in Pharmaceutical Process Research and Development

Multivariate Analysis and Statistics in Pharmaceutical Process Research and Development The application of statistics in pharmaceutical process research and development has evolved significantly over the past decades, motivated in part by the introduction of the Quality by Design paradigm, a landmark change in regulatory expectations for the level of scientific understanding associated with the manufacturing process. Today, statistical methods are increasingly applied to accelerate the characterization and optimization of new drugs created via numerous unit operations well known to the chemical engineering discipline. We offer here a review of the maturity in the implementation of design of experiment techniques, the increased incorporation of latent variable methods in process and material characterization, and the adoption of Bayesian methodology for process risk assessment. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Annual Review of Chemical and Biomolecular Engineering Annual Reviews

Multivariate Analysis and Statistics in Pharmaceutical Process Research and Development

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Publisher
Annual Reviews
Copyright
Copyright © 2017 by Annual Reviews. All rights reserved
ISSN
1947-5438
eISSN
1947-5446
DOI
10.1146/annurev-chembioeng-060816-101418
pmid
28415862
Publisher site
See Article on Publisher Site

Abstract

The application of statistics in pharmaceutical process research and development has evolved significantly over the past decades, motivated in part by the introduction of the Quality by Design paradigm, a landmark change in regulatory expectations for the level of scientific understanding associated with the manufacturing process. Today, statistical methods are increasingly applied to accelerate the characterization and optimization of new drugs created via numerous unit operations well known to the chemical engineering discipline. We offer here a review of the maturity in the implementation of design of experiment techniques, the increased incorporation of latent variable methods in process and material characterization, and the adoption of Bayesian methodology for process risk assessment.

Journal

Annual Review of Chemical and Biomolecular EngineeringAnnual Reviews

Published: Jun 7, 2017

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