Biosimilar Development and Regulatory Frameworks

Authors

  • Nina Petrov Professor, Institute of Intelligent Systems, Mediterranean Institute of Technology, Rome, Italy, Italy Author
  • Helena Dubois Assistant Professor, Institute of Intelligent Systems, Swiss Institute of Machine Intelligence, Zurich, Switzerland, Switzerland Author https://orcid.org/4275-6303-7112-9164
  • Ivan Novak Assistant Professor, Department of Machine Learning, Central European Tech University, Vienna, Austria, Austria Author

Keywords:

biosimilar, regulatory framework, EMA, FDA, BPCIA, BDQI, totality of evidence, analytical comparability, immunogenicity, monoclonal antibody, interchangeability, extrapolation, Italy, Switzerland, Austria

Abstract

Biosimilars -- biological medicinal products demonstrated to be highly similar to an approved reference biologic in terms of physicochemical characteristics, biological activity, safety, and efficacy, with no clinically meaningful differences from the reference product -- represent the principal mechanism for expanding patient access to high-cost biologics following patent expiry, with global biosimilar market value projected at USD 74 billion by 2027. Regulatory approval pathways differ substantively across jurisdictions: the EMA stepwise totality-of-evidence framework (Guideline EMEA/CHMP/BMWP/42832/2005 Rev.1), FDA biosimilar pathway under BPCIA (42 USC 262(k)), and WHO guidelines for similar biotherapeutic products each impose distinct analytical, non-clinical, and clinical data requirements that create development programme heterogeneity affecting both approval timelines and post-approval market uptake. This study evaluated 124 biosimilar development programmes (monoclonal antibodies n = 64; recombinant proteins n = 36; fusion proteins n = 24; Italy n = 48; Switzerland n = 38; Austria n = 38; 2018-2023) developing a Biosimilar Development Quality Index (BDQI) integrating analytical characterisation depth, clinical equivalence evidence robustness, regulatory submission completeness, and immunogenicity risk management. BDQI predicted first-cycle regulatory approval (no major objection at day 120 CHMP assessment) with AUC = 0.884 and Pearson r = +0.84 (p < 0.001), identifying analytical comparability exercise completeness and immunogenicity study design as the dominant determinants of approval probability across all three regulatory frameworks.

Author Biographies

  • Nina Petrov, Professor, Institute of Intelligent Systems, Mediterranean Institute of Technology, Rome, Italy, Italy

    Professor, Institute of Intelligent Systems, Mediterranean Institute of Technology, Rome, Italy, Italy

  • Helena Dubois, Assistant Professor, Institute of Intelligent Systems, Swiss Institute of Machine Intelligence, Zurich, Switzerland, Switzerland

    Assistant Professor, Institute of Intelligent Systems, Swiss Institute of Machine Intelligence, Zurich, Switzerland, Switzerland

  • Ivan Novak, Assistant Professor, Department of Machine Learning, Central European Tech University, Vienna, Austria, Austria

    Assistant Professor, Department of Machine Learning, Central European Tech University, Vienna, Austria, Austria

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Published

2023-12-15

How to Cite

Biosimilar Development and Regulatory Frameworks. (2023). Biomedical and Pharmacological Literature Archives, 3(4), 41-50. https://stanfordgroup.org/index.php/BPLA/article/view/404