How to Utilize Design of Experiment (DoE) Principles for Developing Robust Analytical Methods for QC Environments Jeremy Springall, PhD Introduction Quality by Design (QbD), as currently applied to the manufacturing of biological and biotechnological therapeutic products, constitutes a systematic approach to product development which aims at consistently delivering safe and efficacious products of known quality to patients.1,2 The knowledge obtained during development may be used to support the establishment of an operable design space with suitable process controls. These principles are now being considered for application to analytical methods through what is being termed Analytical Quality by Design (AQbD).3 One can find either partial or full implementation of this systematic approach presented in the literature4,5 highlighting the possible benefits of adopting the AQbD approach for the development and implementation of robust analytical procedures. A vital component of the AQbD approach is to start with the end in mind. This translates to the generation of a predefined analytical target profile (ATP) which explicitly states the intended performance, capability and use of the analytical procedure for ensuring patient safety, manufacturing consistency and efficacy of the product through appropriate monitoring of product critical quality attributes (CQA). The ATP then forms the basis of the generation of the analytical control strategy (ACS).6 The ACS is the sum of steps taken to reduce and/or eliminate risk by ensuring consistent quality of the results generated from the analytical procedure in accordance with the ATP. Development of an appropriate ACS requires us to understand the following three themes; 1) understanding of fit for purpose, 2) understanding of the method as a process and 3) risk management and control. Understanding fit for purpose assists us in generating an appropriate ATP for monitoring any CQAs that could adversely affect the safety, efficacy and manufacturing consistency of the product. Understanding of the method as a process enables analytical scientists to determine what are the critical method performance factors by determining the relationship between possible variables and their effect on the reportable result of the analytical procedure. Risk 4