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Data from measurements over time can be analyzed in different ways. In this article, we compare functional data analysis and nonlinear regression models using, among others, eight information quality dimensions. We present two case studies. The first case study introduces functional data analysis and nonlinear regression models in analyzing dissolution profiles of drug tablets where profiles of tablets under test are compared to reference tablets. A second case study involves statistically designed mixture experiments used in optimization tablet formulation. Python and JMP features are used to demonstrate the methods used in the two case studies.

Functional data analysis and nonlinear regression models: an information quality perspective