A Data Driven Approach to Support Tailored Clinical Programs for Biosimilar Monoclonal Antibodies

Area of Science:

• Biopharmaceutical science
• Regulatory science
• Drug development

Background:

• Biosimilar monoclonal antibodies (mAbs) approved since 2013 reduce costs and improve access.
• Biosimilarity relies on quality attributes (QAs) and bioequivalence, with clinical trials often required.
• European Medicines Agency (EMA) guidelines suggest clinical trials may not always be necessary.

Purpose of the Study:

• To evaluate analytical similarity and the role of clinical data in biosimilarity assessments.
• To analyze quality and clinical data for adalimumab and bevacizumab biosimilars.
• To assess the concordance of biosimilar quality attributes with reference products.

Main Methods:

• Analysis of quality and clinical data packages for 7 adalimumab and 5 bevacizumab biosimilars.
• Determination of biosimilar batch concordance with EU reference product similarity ranges for QAs.
• Review of clinical efficacy and safety data to assess their role in resolving quality concerns.

Main Results:

• Approved adalimumab and bevacizumab biosimilars exhibited varying concordance with EU reference product similarity ranges for quality attributes.
• Clinical efficacy data demonstrated a limited impact on addressing identified quality concerns.
• Significant variability exists in the analytical similarity of approved biosimilar mAbs.

Conclusions:

• A review of clinical data requirements for monoclonal antibody and fusion protein biosimilars is encouraged.
• A quality data-driven approach can facilitate tailored clinical programs for biosimilars.
• Regulatory standards for biosimilar clinical data may need re-evaluation based on analytical similarity.