Chemometrics methods are readily employed in the pharma setting and used to support research, quality control and manufacturing. The predictive methods at the heart of these chemometric approaches, such as PCA / PLS, are machine learning methods.
Understanding process variation is essential for the development of process control strategies and ensuring product quality. Statistical measures on an individual trend by trend basis are relatively easy to demonstrate and provide essential information to understanding (univariate) process variation.
Multivariate analysis provides the tools to deepen process understanding by identifying the potential for process variables to exhibit similar or dissimilar behaviour and/or to have responses classified and predicted with opportunity for real time process monitoring and control.
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