Keywords: Bioassay, Chemistry, manufacturing and controls, Qualificaiton, Robustness
Statistics is a very useful tool in analytical procedures to support drug development and manufacturing. For biological or biotechnology products, bioassay is required for batch release, stability testing or extended characterization. Compared to other analytical methods, bioassays inherit lower throughput and higher variability, which require complex statistical models and deep knowledge to interpret the data. In general, bioassays consist of serial dilutions of a reference standard and testing samples on the same plate. Relative potency is calculated by comparing the reference standard and testing sample using a suitable statistical model. To ensure the quality of bioassay results, system suitability and acceptance criteria need to be determined and the assay needs to be qualified or validated before sample testing. For late stage programs, assay robustness needs to be assessed to estimate variations in the procedural parameters that may potentially affect the assay performance. In this study, how statistics can be applied in assay development, qualification, validation and robustness assessment will be discussed with bioassay case studies for chemistry, manufacturing and controls (CMC).