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The AAPS Journal

, 21:7 | Cite as

The Assessment of Quality Attributes for Biosimilars: a Statistical Perspective on Current Practice and a Proposal

  • Johanna Mielke
  • Franz Innerbichler
  • Martin Schiestl
  • Nicolas M. Ballarini
  • Byron JonesEmail author
Research Article

Abstract

Establishing comparability of the originator and its biosimilar at the structural and functional level, by analyzing so-called quality attributes, is an important step in biosimilar development. The statistical assessment of quality attributes is currently in the focus of attention because both the FDA and the EMA are working on regulatory documents for advising companies on the use of statistical approaches for strengthening their comparability claim. In this paper, we first discuss “comparable” and “not comparable” settings and propose a shift away from the usual comparison of the mean values: we argue that two products can be considered comparable if the range of the originator fully covers the range of the biosimilar. We then introduce a novel statistical testing procedure (the “tail-test”) and compare the operating characteristics of the proposed approach with approaches currently used in practice. In contrast to the currently used approaches, we note that our proposed methodology is compatible with the proposed understanding of comparability and has, compared to other frequently applied range-based approaches, the advantage of being a formal statistical testing procedure which controls the patient’s risk and has reasonable large-sample properties.

KEY WORDS

analytical studies biosimilarity equivalence testing manufacturing change quality attributes 

Notes

Acknowledgments

We are grateful to Muhanned Saeed and Matej Horvat for fruitful discussions. We thank the three reviewers for providing well-thought-out comments which greatly improved this manuscript.

Funding Information

We acknowledge the funding from the European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No 633567 and from the Swiss State Secretariat for Education, Research and Innovation (SERI) under contract number 999754557.

Compliance with Ethical Standards

Disclaimer

The opinions expressed and arguments employed herein do not necessarily reflect the official views of the Swiss Government.

Supplementary material

12248_2018_275_MOESM1_ESM.pdf (99 kb)
ESM 1 (PDF 98 kb)

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Copyright information

© American Association of Pharmaceutical Scientists 2018

Authors and Affiliations

  • Johanna Mielke
    • 1
  • Franz Innerbichler
    • 2
  • Martin Schiestl
    • 2
  • Nicolas M. Ballarini
    • 3
  • Byron Jones
    • 1
    Email author
  1. 1.Novartis Pharma AGBaselSwitzerland
  2. 2.Sandoz GmbHKundlAustria
  3. 3.Section for Medical Statistics, Center for Medical Statistics, Informatics, and Intelligent SystemsMedical University of ViennaViennaAustria

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