Table 2.

Conceptual comparison of the use of statistical tools in clinical studies and analytical comparability

Comparison	Clinical studies	Analytical comparability
Endpoints	One primary endpoint	Multiple endpoints: quality attributes
Evaluation (data collected)	Measure biological reactions to drug	Measure quality attributes of drug
Sources of variation	Variability of biological processing Stratified random sampling	Variability of manufacturing process Difficult to ensure independent data
Acceptance criteria	Margin for primary endpoint based on clinical relevance	Margin based on assay characteristics established by validation studies; different for each quality attribute
Risk of bias	Predefinition of the endpoint and its related statistical evaluation is necessary to mitigate the risk of bias	Endpoints are already set by the CQA assessment, so no risk of bias by selecting the ‘wrong endpoint’
Role of statistics	Statistics required for final determination	Statistics merely a facilitator to describe the degree of residual uncertainty and thus the level of justification needed in case of differences

Adapted from Stangler, 2016 [14]