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Multivariate data analytical techniques (MVA) - Articles and news items


CAMO Software and Stat-Ease, Inc. release software bundle for multivariate data analysis and design of experiments

Supplier news / 29 September 2015 / CAMO Software

CAMO Software, leaders in multivariate data analysis software, and Stat-Ease, Inc., a leading supplier of design of experiments (DOE) software and services, have released a software bundle for multivariate data analysis and design of experiments; The Unscrambler® X Design-Expert® Upgrade…

Whitepaper: Multivariate Data Analysis for Biotechnology and Bio-processing

Whitepapers / 1 October 2013 / CAMO

This free whitepaper gives detailed examples of how these advanced tools can be used in development & discovery, clinical trials, batch monitoring & control, and QA/QC applications.

Implementing chemometrics in late stage development and manufacturing

Implementing chemometrics in late stage development and manufacturing

Issue 2 2012, PAT & QbD / 26 April 2012 / Geir Rune Flåten, former Chemometrician Leader in Global Manufacturing and Supply at GlaxoSmithKline

Chemometrics was defined as a research area in 1974 and developed rapidly through the following decades in parallel with the fast paced improvement in analytical technologies and computational power for lab instruments and sensors. Chemometrics is essentially the translation of measured signals characterising a sample or a process into meaningful results. This is achieved by applying a number of powerful multivariate data analytical techniques (MVA) to develop a model from a representative data set, and use this model to predict or quantify the property of interest for new samples or process runs.

In the pharmaceutical industry, chemometrics has been successfully applied at every stage from discovery, through development, and to manufacturing. In this review, the requirements and benefits to applying chemometrics in late stage development and manufacturing will be discussed.

Two main areas of interest in pharma – ceutical development and manufacturing are QbD (Quality by Design) and PAT (Process Analytical Technologies), and chemometrics, i.e. modelling, is a key element of these approaches. Chemometrics is used for simplicity as the label for any model translating data into meaningful output in the following discussion. To maximise the benefit from chemometrics, the very first step is to define the objective of the model.


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