Analysis of imprecision in incurred sample reanalysis for small molecules.

Over the years, incurred sample (IS) reanalysis (ISR) has become a tool to confirm the reliability of bioanalytical measurements. The recommendation for ISR acceptance criterion for small molecules is at least 67% of ISR samples that have reanalyzed concentrations within 20% of their original concentrations when normalized to their means. To understand the relevance of the ISR acceptance criterion and sample size requirements, simulated ISR studies evaluated the probability of ISR studies passing the acceptance criterion (ISR pass rate) as a function of IS imprecision and sample size. When IS imprecision (percent coefficient of variation: %CV) is low (≤ 10 or 1-10% CV), high ISR pass rate (≥ 99%) is attained with <50 samples. At intermediate IS imprecision (e.g., 12% CV or 7-12% CV range), 80-160 samples are required for a high ISR pass rate. When IS imprecision is at the higher end of the acceptance limit, ISR pass rate decreases significantly, and increasing sample size fails to achieve high ISR pass rate. The effect of systematic bias (e.g., instability, interconversion) on ISR pass rate is strongly dependent on sample size at intermediate IS imprecision. The results provide an understanding of the effect of IS imprecision on ISR pass rates and a framework for selection of ISR sample sizes.

Implementation of a reference-scaled average bioequivalence approach for highly variable generic drug products by the US Food and Drug Administration.

Highly variable (HV) drugs are defined as those for which within-subject variability (%CV) in bioequivalence (BE) measures is 30% or greater. Because of this high variability, studies designed to show whether generic HV drugs are bioequivalent to their corresponding HV reference drugs may need to enroll large numbers of subjects even when the products have no significant mean differences. To avoid unnecessary human testing, the US Food and Drug Administration's Office of Generic Drugs developed a reference-scaled average bioequivalence (RSABE) approach, whereby the BE acceptance limits are scaled to the variability of the reference product. For an acceptable RSABE study, an HV generic drug product must meet the scaled BE limit and a point estimate constraint. The approach has been implemented successfully. To date, the RSABE approach has supported four full approvals and one tentative approval of HV generic drug products.

Comparing generic and innovator drugs: a review of 12 years of bioequivalence data from the United States Food and Drug Administration.

BACKGROUND: In the US, manufacturers seeking approval to market a generic drug product must submit data demonstrating that the generic formulation provides the same rate and extent of absorption as (ie, is bioequivalent to) the innovator drug product. Thus, most orally administered generic drug products in the US are approved based on results of one or more clinical bioequivalence studies. OBJECTIVE: To evaluate how well the bioequivalence measures of generic drugs approved in the US over a 12-year period compare with those of their corresponding innovator counterparts. METHODS: This retrospective analysis compared the generic and innovator bioequivalence measures from 2070 single-dose clinical bioequivalence studies of orally administered generic drug products approved by the Food and Drug Administration (FDA) from 1996 to 2007 (12 y). Bioequivalence measures evaluated were drug peak plasma concentration (C(max)) and area under the plasma drug concentration versus time curve (AUC), representing drug rate and extent of absorption, respectively. The generic/innovator C(max) and AUC geometric mean ratios (GMRs) were determined from each of the bioequivalence studies, which used from 12 to 170 subjects. The GMRs from the 2070 studies were averaged. In addition, the distribution of differences between generic means and innovator means was determined for both C(max) and AUC. RESULTS: The mean +/- SD of the GMRs from the 2070 studies was 1.00 +/- 0.06 for C(max) and 1.00 +/- 0.04 for AUC. The average difference in C(max) and AUC between generic and innovator products was 4.35% and 3.56%, respectively. In addition, in nearly 98% of the bioequivalence studies conducted during this period, the generic product AUC differed from that of the innovator product by less than 10%. CONCLUSIONS: The criteria used to evaluate generic drug bioequivalence studies support the FDA's objective of approving generic drug formulations that are therapeutically equivalent to their innovator counterparts.

Highly variable drugs: observations from bioequivalence data submitted to the FDA for new generic drug applications.

INTRODUCTION: It is widely believed that acceptable bioequivalence studies of drugs with high within-subject pharmacokinetic variability must enroll higher numbers of subjects than studies of drugs with lower variability. We studied the scope of this issue within US generic drug regulatory submissions. MATERIALS AND METHODS: We collected data from all in vivo bioequivalence studies reviewed at FDA's Office of Generic Drugs (OGD) from 2003-2005. We used the ANOVA root mean square error (RMSE) from bioequivalence statistical analyses to estimate within-subject variability. A drug was considered highly variable if its RMSE for C (max) and/or AUC was > or =0.3. To identify factors contributing to high variability, we evaluated drug substance pharmacokinetic characteristics and drug product dissolution performance. RESULTS AND DISCUSSION: In 2003-2005, the OGD reviewed 1,010 acceptable bioequivalence studies of 180 different drugs, of which 31% (57/180) were highly variable. Of these highly variable drugs, 51%, 10%, and 39% were either consistently, borderline, or inconsistently highly variable, respectively. We observed that most of the consistent and borderline highly variable drugs underwent extensive first pass metabolism. Drug product dissolution variability was high for about half of the inconsistently highly variable drugs. We could not identify factors causing variability for the other half. Studies of highly variable drugs generally used more subjects than studies of lower variability drugs. CONCLUSION: About 60% of the highly variable drugs we surveyed were highly variable due to drug substance pharmacokinetic characteristics. For about 20% of the highly variable drugs, it appeared that formulation performance contributed to the high variability.

Bioequivalence approaches for highly variable drugs and drug products.

Over the past decade, concerns have been expressed increasingly regarding the difficulty for highly variable drugs and drug products (%CV greater than 30) to meet the standard bioequivalence (BE) criteria using a reasonable number of study subjects. The topic has been discussed on numerous occasions at national and international meetings. Despite the lack of a universally accepted solution for the issue, regulatory agencies generally agree that an adjustment of the traditional BE limits for these drugs or products may be warranted to alleviate the resource burden of studying relatively large numbers of subjects in bioequivalence trials. This report summarizes a careful examination of all the statistical methods available and extensive simulations for BE assessment of highly variable drugs/products. Herein, the authors present an approach of scaling an average BE criterion to the within-subject variability of the reference product in a crossover BE study, together with a point-estimate constraint imposed on the geometric mean ratio between the test and reference products. The use of a reference-scaling approach involves the determination of variability of the reference product, which requires replication of the reference treatment in each individual. A partial replicated-treatment design with this new data analysis methodology will thus provide a more efficient design for BE studies with highly variable drugs and drug products.