Developing a Statistical Approach to Facilitate Sameness Assessment of Complex Heterogenous Active Pharmaceutical Ingredients

• Activity Number: 372 - SPEED: SPAAC SESSION IV
• Type: Topic-Contributed
• Date/Time: Thursday, August 12, 2021 : 12:00 PM to 1:50 PM
• Sponsor: International Chinese Statistical Association
• Author(s): Yu-Ting Weng* and Meng Hu and Liang Zhao and Chao Wang and Meiyu Shen and Xiajing Gong
• Companies: U.S. Food and Drug Administration and U.S. Food and Drug Administration and U.S. Food and Drug Administration and U.S. Food and Drug Administration and Office of Biostatistics CDER, FDA and U.S. Food and Drug Administration
• Keywords: Equivalence tests; Multivariate analysis; Hierarchical Sampling; API sameness

Abstract

The assessment of active pharmaceutical ingredient (API) sameness between a test product and the reference listed drug (RLD) product is a key component of pharmaceutical equivalence assessment for generic products. API sameness assessment can be challenging since the API sameness assessment often involves analytical methods that generate complex multi-dimensional data for assessment. Thus, one challenge for demonstrating API sameness is the comparison of generated multi-dimensional data from the test and reference products. In this study, we developed a two-stage statistical approach to conduct quantitative assessment of API sameness for drug products with complex heterogenous API mixtures. Briefly, in Stage 1, an equivalence testing for summation of all API components is considered and a well-accepted margin is applied. In Stage 2, we constructed a statistical model to describe the measured data from the RLD product. Subsequently, we developed a multivariate statistical equivalence test to compare multi-dimensional data from Test and RLD products. Given the simulated data and developed test, statistical criteria were evaluated and established to reach reasonable type I/II errors.