title: Multivariate analysis in the pharmaceutical industry: enabling process understanding and improvement in the PAT and QbD era.
abstract: In the pharmaceutical industry, chemometrics is rapidly establishing itself as a tool that can be used at every step of product development and beyond: from early development to commercialization. This set of multivariate analysis methods allows the extraction of information contained in large, complex data sets thus contributing to increase product and process understanding which is at the core of the Food and Drug Administration's Process Analytical Tools (PAT) Guidance for Industry and the International Conference on Harmonisation's Pharmaceutical Development guideline (Q8). This review is aimed at providing pharmaceutical industry professionals an introduction to multivariate analysis and how it is being adopted and implemented by companies in the transition from "quality-by-testing" to "quality-by-design". It starts with an introduction to multivariate analysis and the two methods most commonly used: principal component analysis and partial least squares regression, their advantages, common pitfalls and requirements for their effective use. That is followed with an overview of the diverse areas of application of multivariate analysis in the pharmaceutical industry: from the development of real-time analytical methods to definition of the design space and control strategy, from formulation optimization during development to the application of quality-by-design principles to improve manufacture of existing commercial products.
authors.affiliation: Department of Drug Product Science & Technology, Bristol-Myers Squibb , Reeds Lane, Moreton, Wirral , UK.
authors.forename: Ana P
authors.initials: AP
authors.lastname: Ferreira
authors.forename: Mike
authors.initials: M
authors.lastname: Tobyn
mesh_terms: D004345:Drug Industry; D006801:Humans; D016018:Least-Squares Analysis; D015999:Multivariate Analysis; D025341:Principal Component Analysis; D011786:Quality Control; D013678:Technology, Pharmaceutical / Q000379:methods*; D014481:United States; D014486:United States Food and Drug Administration
keywords: Partial least squares regression; principal component analysis; process analytical technology; quality by design