ABSTRACT
This chapter describes statistical methods for identification of critical quality attribute (CQA) via the study of the link between CQAs and clinical outcome. It reviews stepwise approach for demonstrating biosimilarity. Under a well-established relationship between CQAs and clinical outcomes, the chapter discusses a couple of proposed criteria for classification of identified CQAs based on its criticality and/or risking raking. To identify CQAs in a manufacturing process of biosimilar drug products, the link between CQAs and clinical outcomes in terms of safety, purity, and potency are necessarily established. The chapter proposes statistical methods based on multivariate regression analysis for determining design space. It focuses on two traditional approaches: overlapping mean response surfaces and the composite desirability function. The tier approach first assesses the criticality or risk ranking of the CQAs relevant to clinical outcome and classify these CQAs to appropriate tiers depending upon their impact on clinical outcomes.
