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Nonparametric Tests for Evaluation of Biosimilarity in Variability of Follow-on Biologics.

Authors :
Zhang, Nan
Yang, Jun
Chow, Shein-Chung
Chi, Eric
Source :
Journal of Biopharmaceutical Statistics. Nov2014, Vol. 24 Issue 6, p1239-1253. 15p.
Publication Year :
2014

Abstract

As more biologic products are going off patent protection, the development of follow-on biologic products (also known as biosimilars) has gained much attention from both the biotechnology industry and regulatory agencies. Unlike small molecules, the development of biologic products is not only more complicated but also sensitive to a small change in procedure/environment during the manufacturing process. In practice, biologics are expected to have much larger variation, which will potentially impact the product quality and potency. Thus, it is suggested that the assessment of biosimilarity between biologic products should take variability into consideration, in addition to average biosimilarity of endpoints of interest. In this article, we propose the use of nonparametric tests for evaluation of biosimilarity in variability between the follow-on biologic product and the reference product. Extensive simulations are conducted to compare the relative performance of the proposed methods with the adapted parametric F-test in terms of correctly concluding biosimilarity in variability. Under normality assumption, the proposed nonparametric tests are found to be comparably well with the adapted F-test. However, the proposed methods are more robust when the assumption is violated. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10543406
Volume :
24
Issue :
6
Database :
Academic Search Index
Journal :
Journal of Biopharmaceutical Statistics
Publication Type :
Academic Journal
Accession number :
99195504
Full Text :
https://doi.org/10.1080/10543406.2014.941991