Stan Altan, J&J Pharmaceutical R&D; Jim Bergum, Bristol-Myers Squibb Company; Lori Pfahler, Merck & Co.; Edith Senderak, Merck and Co;  Shanthi Sethuraman, Lilly Reserach Laboratories; and  Kim Erland Vukovinsky, Pfizer. All authors are members of the PhRMA CMC SET.

Design Space is part of FDA’s quality initiative for the 21st century to move towards a new paradigm for pharmaceutical assessment as outlined in ICH Q8, Q9, Q10.  The statistics for design space development plays an important role in ensuring the robustness of this approach. The objective of this paper is to provide concise answers to frequently asked questions related to the statistical aspects of determining a design space as part of the QbD initiatives.  In this paper, we discuss the statistical tools used in the following: experimental planning and strategy including the use, analysis and interpretation of historical information, the analysis of a statistically designed experiment (DOE), defining a DS based on the results of the DOE, evaluating the resulting DS and graphical representation of the DS.  These questions and answers are not meant to be exhaustive or completely detailed, but do cover a broad range and detail to be useful to the practicing scientist or process engineer.

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