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Development of Quantitative Comparative Approaches to Support Complex Generic Drug Development

  • Yuqing Gong,
  • Francis-Xavier Barretto,
  • Yi Tsong,
  • Youssef Mousa,
  • Ke Ren,
  • Darby Kozak,
  • Meiyu Shen,
  • Meng Hu,
  • Liang Zhao

摘要

On October 27–28, 2022, the US Food and Drug Administration (FDA) and the Center for Research on Complex Generics (CRCG) hosted a virtual public workshop titled “Best Practices for Utilizing Modeling Approaches to Support Generic Product Development.” This report summarizes the presentations and panel discussions for a session titled “Development of Quantitative Comparative Approaches to Support Complex Generic Drug Development.” This session featured speakers and panelists from both the generic industry and the FDA who described applications of advanced quantitative approaches for generic drug development and regulatory assessment within three main topics of interest: (1) API sameness assessment for complex generics, (2) particle size distribution assessment, and (3) dissolution profile similarity comparison. The key takeaways were that the analysis of complex data poses significant challenges to the application of conventional statistical bioequivalence methods, and there are various opportunities for using data analytics approaches for developing and applying suitable equivalence assessment method.

Graphical Abstract