title: Statistical considerations in biosimilar assessment using biosimilarity index.
abstract: When an innovative biologic product goes off patent, biopharmaceutical or biotechnological companies may file an application for regulatory approval of biosimilar products. Unlike small molecule drug products, biosimilars are not exact copies of their brand-name counterpart, and they are usually very sensitive to changes in environmental factors and have greater variabilities due to their complexity and sensitivity to variation in manufacturing processes. Facing these challenges, a biosimilarity index based on reproducibility probability is proposed to assess biosimilarity. In this article, we have demonstrated how to assess biosimilarity between the test and reference product in relative to a reference standard that is established in a study where reference product is compared with itself. Biosimilairty index approach is robust against biosimilarity criteria and has the advantage of allowing the assessment of the degree of similarity.
authors.affiliation: Aijing Zhang is a graduate student, Jung-Ying Tzeng is an Associate Professor in the Department of Statistics at NC State University, Raleigh, NC 27695, Shein-Chung Chow is a Professor in the Department of Bioinformatics and Biostatistics at Duke University, Durham, NC 27708.
authors.forename: Aijing
authors.initials: A
authors.lastname: Zhang
authors.affiliation: Aijing Zhang is a graduate student, Jung-Ying Tzeng is an Associate Professor in the Department of Statistics at NC State University, Raleigh, NC 27695, Shein-Chung Chow is a Professor in the Department of Bioinformatics and Biostatistics at Duke University, Durham, NC 27708.
authors.forename: Jung-Ying
authors.initials: JY
authors.lastname: Tzeng
authors.affiliation: Aijing Zhang is a graduate student, Jung-Ying Tzeng is an Associate Professor in the Department of Statistics at NC State University, Raleigh, NC 27695, Shein-Chung Chow is a Professor in the Department of Bioinformatics and Biostatistics at Duke University, Durham, NC 27708.
authors.forename: Shein-Chung
authors.initials: SC
authors.lastname: Chow
keywords: Biosimilarity Index; Degree of Similarity; Highly Similar; Reproducibility Probability