Statistical Tests for Bioequivalence and Biosimilarity

Statistical testing for bioequivalence (BE) represents a rapidly evolving field that combines fundamental statistical principles with cutting-edge regulatory science methodologies. As an expert with over a decade of FDA experience reviewing BE applications, this course addresses the critical need for practicing statisticians to master novel analytical approaches in generic drug and biosimilar product evaluation. This professional development opportunity presents state-of-the-art techniques including adaptive Mixed Scaled Average Bioequivalence (a-MSABE), advanced mixed modeling for longitudinal biosimilar data, and innovative AI/ML applications in late-stage drug development—methods that are transforming how statisticians approach regulatory submissions. The course covers emerging challenges that FDA and industry statisticians face daily: managing highly variable drug performance, addressing data integrity issues, optimizing sample sizes through adaptive designs, and implementing robust statistical solutions for complex study designs. Through real-world case studies from approved FDA applications, participants will gain practical expertise in applying novel methodologies across diverse product types and therapeutic areas. This specialized field has experienced tremendous growth due to increased generic drug approvals and expanding biosimilar markets. Participants will acquire essential tools to enhance productivity and efficiency in pharmaceutical development while preparing them to thrive in an increasingly complex regulatory environment where statistical innovation drives decision-making.