Showing analytical similarity is key to license biosimilar products with reduced or circumvented clinical effort. Statistical procedures to assess analytical similarity of quality attributes at drug product level have been highly debated by academia, industry, and regulatory agencies. In the past, a tiered approach was recommended by regulators, consisting of equivalence tests and quality range tests. However, this approach has recently been withdrawn by FDA. New guidelines of FDA and EMA favour the usage of quality range tests. Moreover, it has recently been shown that simple range tests, such as the 3SD test, are flawed, since they do not control the agency risk of falsely declaring a non-biosimilar product as being biosimilar (Type I error). This has also been highlighted by regulators recently. In this contribution, we developed a novel bootstrapping test for assessing analytical similarity that overcomes current flaws of equivalence and range tests. The developed test shows the desired properties, that is, (i) similarity conditions can be easily defined, (ii) differences of mean and the variance between the biosimilar and the innovator can be studied simultaneously, and (iii) the Type I error of the test can be controlled at a low level, e.g. 5%, evenly along the entire similarity condition. Moreover, the test shows up to 10% higher mean power values in the similarity region compared to existing range tests that aim to control the Type I error. Hence, this test is superior to existing quality range tests and is perceived compliant with current regulatory requirements.
Keywords: analytical similarity; biosimilar; biosimilarity; bootstrapping; equivalence tests; range test.
© 2022. The Author(s).