need to be added to the design to improve the model fit through augmentation. Additionally, if curvature is observed then additional experimentation would be required to be able to accurately model the curvature present and then give us confidence in the predictive power of the model determined for the reportable results obtained. Once a good model fit is obtained and we have sufficient confidence in the predictive power of the model for the design space under investigation we can then start to determine our method operable design region (MODR) (Figure 3) for the critical method attributes through robustness studies and then define our final analytical procedure conditions noted in the SOP or technical document. Prior to authoring, review and approval of the SOP with the new analytical procedure information it is very important to perform a robustness assessment of the final optimized conditions to reduce the risk of possible future analytical procedure failures. As mentioned previously, for the optimization step Figure 2. Results from the fractional factorial model design used for method optimization. The strong linear correlation observed between the predicted and actual data indicates the model has a strong predictive power. Figure 3. Contour maps from the DoE for study for sample preparation optimization. The robust method operable design region (MODR) is highlighted by the red squares. 7