‘Reduced method robustness testing of analytical methods driven by a risk-based approach’ by Phil Borman, Marion Chatfield, Patrick Jackson, Alice Laures, and George Okafo in Pharmaceutical Technology Europe, Volume 4, Issue 22
This article details an interesting approach to reducing the number of factors investigated during a robustness study. Basically the factors which are chosen to be studied in an experimental design are further reduced by performing a risk analysis of each factor and combining factors where possible. As we hear more and more about addressing method robustness earlier in the method development process as part of Quality by Design, more efficient approaches to performing these studies become desirable.
The thing that stands out for me about this article, and indeed all discussions of robustness, is that although the statistics and design of experiments is very important (and I think this article describes these quite well) the most important contribution to robustness testing comes from the experience of the analyst who understands the actual effects of the factors involved and can identify those which are most important. The risk assessment performed in the case study described in this article was performed by ‘GC experts’. Without this contribution the studies cannot produce meaningful results.