Y. Vander Heyden

Screening for important factors during method optimization or in robustness testing involves two-level screening designs, such as fractional factorial and Plackett–Burman designs, as described in Part 1. This second part on screening designs discusses the experimental protocol for executing these designs and the data analysis of their results.

In a good laboratory practice (GLP) environment, data-handling software cannot be used until it is validated. This even applies to the most simple program that performs calculations or stores data. A detailed documentation of the set-up and the performance of the software - called software validation - is required. The development and validation requirements are described in this article and illustrated with a software for robustness testing (SRT), which guides the user step-by-step through the experimental set-up and interpretation of robustness tests. This software was developed in an Excel (Windows XP) environment and is used as part of method validation in laboratories that require compliance with GLP and 21 CFR Part 11. The software was subjected to software validation regulations and is compliant with electronic records and signature rules (21 CFR Part 11) as it creates, delivers and stores electronic data. The validation tests are based on the computerized system validation (CSV) -..

It would help to have a restricted set of chromatographic systems (CS) that together serve as potential starting points in method development.

The second part in this series focuses on the variables in large data tables, looking at the vocabulary used by PCA experts, and explaining some of the background to the method. It further provides practical examples of how these variables operate in practice.

In this, the first of a two-part series, the authors provide some background on the PCA method and introduce some of the terminology used by practitioners of the method.

In the first instalment of this new column, Massart and Vander Heyden review the subject of chemometrics, and in particular its relevance to separation science. The column aims to explain how application of chemometrical techniques can improve both the design of robust analytical methods and the subsequent interpretation of derived results.