Strategy to equivalence testing for development and scale up of biopharmaceutical downstream processes

Efficient development for multistep downstream processing of biopharmaceuticals depends on fast and robust transfer from bench to manufacturing-scale. Equivalence tests are used to assess the impact of changes in product quality and quantity during process development, optimization and production. This article presents the results of a simulation study comparing the impact of sample sizes, data distributions, variances and equivalence acceptance criteria (EAC) on the performance of equivalence tests. Our results show that a sample size of at least four in the reference group was the minimum recommended size to obtain an acceptable overall performance. Reference data should be evaluated for outliers prior to the equivalence tests and reliable test decisions are only taken with a low variance in the data of the reference group using the EAC proposed by Limentani. Considering these recommendations we obtained a reliable product yield comparability after chromatographic purification of a biopharmaceutical in bench and manufacturing-scale.