Generalized Subset Designs in Analytical Chemistry
Artikel i vetenskaplig tidskrift, 2017

Design of experiments (DOE) is an established methodology in research, development, manufacturing, and production for screening, optimization, and robustness testing. Two-level fractional factorial designs remain the preferred approach due to high information content while keeping the number of experiments low. These types of designs, however, have never been extended to a generalized multilevel reduced design type that would be capable to include both qualitative and quantitative factors. In this Article we describe a novel generalized fractional factorial design. In addition, it also provides complementary and balanced subdesigns analogous to a fold-over in two-level reduced factorial designs. We demonstrate how this design type can be applied with good results in three different applications in analytical chemistry including (a) multivariate calibration using microwave resonance spectroscopy for the determination of water in tablets, (b) stability study in drug product development, and (c) representative sample selection in clinical studies. This demonstrates the potential of generalized fractional factorial designs to be applied in many other areas of analytical chemistry where representative, balanced, and complementary subsets are required, especially when a combination of quantitative and qualitative factors at multiple levels exists.

Orthogonal Arrays

Tablet Formulation

Multivariate Calibration

Författare

I. Surowiec

Umea universitet

Ludvig Vikström

Chalmers, Matematiska vetenskaper

Göteborgs universitet

Gustaf Hector

Chalmers, Matematiska vetenskaper

Göteborgs universitet

E. Johansson

Sartorius Stedim Data Analytics AB

C. Vikstrom

Sartorius Stedim Data Analytics AB

J. Trygg

Umea universitet

Sartorius Stedim Data Analytics AB

Analytical Chemistry

0003-2700 (ISSN) 1520-6882 (eISSN)

Vol. 89 6491-6497

Ämneskategorier

Analytisk kemi

DOI

10.1021/acs.analchem.7b00506