Different multivariate approaches to material discovery, process development, PAT and environmental process monitoring

The aim with the present paper is to illustrate the use of multivariate strategies (i.e. integration of different multivariate methods) with five examples, four from the pharmaceutical industry and one from environmental research. In the first part, two examples wherein hierarchical models are applied to quality control (QC) and process control are discussed. In the second part a more complex problem and a strategy for material discovery/development are presented wherein a combination of multivariate calibration, multivariate analysis and multivariate design is needed. In the third part, a process analytical/optimization problem is illustrated with a two-step process, demanding that different multivariate tools are combined in a sequential way so that a useful model can be established and the process can be understood. In the final part the usefulness of principal component analysis followed by soft independent modelling of class analogy is illustrated with an example from environmental process monitoring. The five examples from quite different areas show that the chemometric tools are even more powerful if used integrated. However, different strategies and combinations of the tools have to be applied, depending on the problem and the aim.

Gabrielsson, JonUmeå universitet,Kemiska institutionen (författare)
Olsman, Helena (författare)
Seifert, Elisabeth (författare)
Petterssen, Jarle (författare)
Lek, Per M. (författare)
Boman, Arne (författare)
Lundstedt, TorbjörnUppsala universitet,Institutionen för läkemedelskemi(Swepub:uu)tolun677 (författare)
Uppsala universitetEkotoxikologi (creator_code:org_t)

Ingår i:Chemometrics and Intelligent Laboratory Systems: Elsevier BV84:1-2, s. 201-2070169-74391873-3239

Av författaren/redakt...: Lundstedt-Enkel, ...; Gabrielsson, Jon; Olsman, Helena; Seifert, Elisabe ...; Petterssen, Jarl ...; Lek, Per M.; visa fler...; Boman, Arne; Lundstedt, Torbj ...; visa färre...

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