Determination of bioequivalence (BE), a crucial part of the evaluation of generic drugs, may depend on clinical endpoint studies, pharmacokinetic (PK) studies of bioavailability, and In-Vitro tests, among others. Additionally, in reviewing Abbreviated New Drug Applications (ANDA), FDA reviewers often analyze safety studies and perform various kinds of simulations. A growing, vibrant group of statisticians in the Office of Biostatistics, CDER/FDA has adopted R for both their routine tasks and to address numerous scientific questions that are received in the form of internal consults. During the past 5 years, we have used R to run power simulations; generate the distribution of certain statistics of interest; assess the similarity of and cluster amino-acid sequences as well as, derive the distribution of the molecular weight of such sequences of a certain length; and determine the validity of data sets categorized for genotoxicity. R-package SABE was developed to accompany a new statistical test, used to assess BE of topical dermatological products when data for evaluation come from the In-Vitro Permeation Test (IVPT) [1]. BE tests consider comparisons between a Test (usually generic) and a Reference (RLD) product under a replicate study design. A function that assesses BE of a Test and a Reference formulation uses a mixed scaled criterion for the PK metrics AUC (Area Under the Curve) and Cmax (maximum concentration).
Elena Rantou
FDA
Using R for Generic Drug Evaluation and SABE R-package for Assessing Bioequivalence of Topical Dermatological Products
Determination of bioequivalence (BE), a crucial part of the evaluation of generic drugs, may depend on clinical endpoint studies, pharmacokinetic (PK) studies of bioavailability, and In-Vitro tests, among others. Additionally, in reviewing Abbreviated New Drug Applications (ANDA), FDA reviewers often analyze safety studies and perform various kinds of simulations. A growing, vibrant group of statisticians in the Office of Biostatistics, CDER/FDA has adopted R for both their routine tasks and to address numerous scientific questions that are received in the form of internal consults. During the past 5 years, we have used R to run power simulations; generate the distribution of certain statistics of interest; assess the similarity of and cluster amino-acid sequences as well as, derive the distribution of the molecular weight of such sequences of a certain length; and determine the validity of data sets categorized for genotoxicity. R-package SABE was developed to accompany a new statistical test, used to assess BE of topical dermatological products when data for evaluation come from the In-Vitro Permeation Test (IVPT) [1]. BE tests consider comparisons between a Test (usually generic) and a Reference (RLD) product under a replicate study design. A function that assesses BE of a Test and a Reference formulation uses a mixed scaled criterion for the PK metrics AUC (Area Under the Curve) and Cmax (maximum concentration).