A Functional Metric Approach to Assess Biosimilarity With Application to Rheumatoid Arthritis Trials. (2nd April 2020)

• Record Type: Journal Article
• Authors: Ghosh, Sujit K.; Dong, Lin
• Is Part Of: Statistics in biopharmaceutical research. Volume 12:Number 2(2020)
• Page Start: 234
• Page End: 243
• Publication Date: 2020-04-02
• Subjects: Bernstein polynomials -- Binary responses -- Rheumatic arthritis -- Semiparametric models; Pharmacy -- Statistical methods -- Periodicals; Pharmaceutical biotechnology -- Statistical methods -- Periodicals; Biopharmaceutics -- Periodicals; Biometry -- Periodicals; Pharmacy -- Statistical methods; Periodicals; 615.190727
• DOI: 10.1080/19466315.2020.1733071
• Languages: English
• ISSNs: 1946-6315

Abstract

Abstract: In recent years there has been a lot of interest to test for similarity between biological drug products, commonly known as biologics. Biologics are large and complex molecule drugs that are produced by living cells and hence these are sensitive to the environmental changes. In addition, biologics usually induce antibodies which raise the safety and efficacy issues. The manufacturing process is also much more complicated and often costlier than the small-molecule generic drugs. Because of these complexities and inherent variability of the biologics, the testing paradigm of the traditional generic drugs cannot be directly used to test for biosimilarity. Taking into account some of these concerns we propose a functional distance based methodology that takes into consideration the entire time course of the study and is based on a class of flexible semiparametric models. The empirical results show that the proposed approach is more sensitive than the classical equivalence tests approach which are usually based on arbitrarily chosen time point. Bootstrap based methodologies are also presented for statistical inference.