COMPARING DISTRIBUTIONS OF SHELF LIVES FOR DRUG PRODUCTS WITH TWO COMPONENTS UNDER DIFFERENT DESIGNS

To reduce the cost of stability testing in drug research and development, both bracketing and matrixing designs are recommended in the U.S. Food and Drug Administration's (FDA) guidelines for drug products with a single active ingredient (component). When the drug product contains multiple active components, the naïve approach is to take the minimum of shelf lives obtained from individual components as the labeled shelf life. The purpose of this article is to compare the distributions of the shelf life obtained as the minimum shelf life of two components for full FDA's sampling plan, matrixing, and bracketing designs. The results were obtained based on theoretical considerations and simulation studies.     

A NOTE ON SAMPLE SIZE CALCULATION FOR MEAN COMPARISONS BASED ON NONCENTRAL t-STATISTICS

One-sample and two-sample t-tests are commonly used in analyzing data from clinical trials in comparing mean responses from two drug products. During the planning stage of a clinical study, a crucial step is the sample size calculation, i.e., the determination of the number of subjects (patients) needed to achieve a desired power (e.g., 80%) for detecting a clinically meaningful difference in the mean drug responses. Based on noncentral t-distributions, we derive some sample size calculation formulas for testing equality, testing therapeutic noninferiority/superiority, and testing therapeutic equivalence, under the popular one-sample design, two-sample parallel design, and two-sample crossover design. Useful tables are constructed and some examples are given for illustration.     

Assessing bioequivalence and drug interchangeability

ABSTRACT

As indicated by the US Food and Drug Administration (FDA), approved generic drug products can be used as substitutes for their respective innovative drug products. The FDA, however, does not indicate that two generic copies of the same innovative drug can be used interchangeably, even though they have been shown to be bioequivalent to the same innovative drug product. As more and more generic drug products become available in the market place, it is a concern whether these approved generic drug products have the same quality and safety/efficacy and hence can be used interchangeably. To address the issue of drug interchangeability, several criteria such as individual bioequivalence criterion, a criterion based on the variability due to subject-by-drug interaction, and a scaled criterion for drug interchangeability (SCDI) have been proposed in the literature. In this article, the performances of these criteria, including a newly proposed reversed average bioequivalence criterion, are studied under a 2x4 replicated crossover design in terms of the percentage of passing at the best and worst possible scenarios of similarity. The goal of this paper is to investigate the interchangeability in terms of switchability between a generic (test) drug product and an originator (reference) drug product.