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Title: Comparative Analyses of Bioequivalence Assessment Methods for In Vitro Permeation Test Data

Journal Article · · Pharmaceutical Statistics
DOI: https://doi.org/10.1002/pst.2434 · OSTI ID:2513589
ORCiD logo [1];  [2];  [2];  [2];  [2]
  1. Department of Biostatistics and Computational Biology University of Rochester Rochester New York USA
  2. Office of Biostatistics, Office of Translational Science, Center for Drug Evaluation and Research US Food and Drug Administration Silver Spring Maryland USA

ABSTRACT For topical, dermatological drug products, an in vitro option to determine bioequivalence (BE) between test and reference products is recommended. In particular, in vitro permeation test (IVPT) data analysis uses a reference‐scaled approach for two primary endpoints, cumulative penetration amount (AMT) and maximum flux ( J max ), which takes the within donor variability into consideration. In 2022, the Food and Drug Administration (FDA) published a draft IVPT guidance that includes statistical analysis methods for both balanced and unbalanced cases of IVPT study data. This work presents a comprehensive evaluation of various methodologies used to estimate critical parameters essential in assessing BE. Specifically, we investigate the performance of the FDA draft IVPT guidance approach alongside alternative empirical and model‐based methods utilizing mixed‐effects models. Our analyses include both simulated scenarios and real‐world studies. In simulated scenarios, empirical formulas consistently demonstrate robustness in approximating the true model, particularly in effectively addressing treatment–donor interactions. Conversely, the effectiveness of model‐based approaches heavily relies on precise model selection, which significantly influences their results. The research emphasizes the importance of accurate model selection in model‐based BE assessment methodologies. It sheds light on the advantages of empirical formulas, highlighting their reliability compared to model‐based approaches and offers valuable implications for BE assessments. Our findings underscore the significance of robust methodologies and provide essential insights to advance their understanding and application in the assessment of BE, employed in IVPT data analysis.

Sponsoring Organization:
USDOE
OSTI ID:
2513589
Journal Information:
Pharmaceutical Statistics, Journal Name: Pharmaceutical Statistics Journal Issue: 1 Vol. 24; ISSN 1539-1604
Publisher:
Wiley Blackwell (John Wiley & Sons)Copyright Statement
Country of Publication:
Country unknown/Code not available
Language:
English

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