It is highly impractical to evaluate the impact of all possible parameters on the output of the
method. Therefore, robustness studies could be limited to the demonstration that the
reported assay values are not affected by small variations of “essential” operational
parameters. It is a good practice to prospectively establish a general design (outline) for such
studies. Typically, in these types of studies a reference standard and/or other appropriate
samples are analyzed at the nominal load. The studies may be carried out using the onefactor-
at-a-time approach or a Design of Experiment (DOE) approach. The selection of assay
parameters can vary according to the method type and capabilities of the factorial design, if
applicable. It is essential to study the impact of all essential factors, and it is important to
establish prospectively “target expectations” for acceptable changes in the output, to ensure
that these robustness studies do not repeat the development work. The maximum allowable change in the output of the analytical method can be linked to the target expectations for the
precision of the method, which are derived from the Horwitz equation (Horwitz 1982;
Horwitz and Albert 1997; Horwitz and Albert 1997). Recently a number of software
packages have become available to assist with the design and data analysis (Turpin,
Lukulay et al. 2009; Jones and Sall 2011; Karmarkar, Garber et al. 2011).