Dale P. Conner

Biopharmaceutics classification system: the scientific basis for biowaiver extensions.

The current BSC guidance issued by the FDA allows for biowaivers based on conservative criteria. Possible new criteria and class boundaries are proposed for additional biowaivers based on the underlying physiology of the gastrointestinal tract. The proposed changes in new class boundaries for solubility and permeability are as follows: 1. Narrow the required solubility pH range from 1.0-7.5 to 1.0-6.8. 2. Reduce the high permeability requirement from 90% to 85%. The following new criterion and potential biowaiver extension require more research: 1. Define a new intermediate permeability class boundary. 2. Allow biowaivers for highly soluble and intermediately permeable drugs in IR solid oral dosage forms with no less than 85% dissolved in 15 min in all physiologically relevant dissolution media, provided these IR products contain only known excipients that do not affect the oral drug absorption. The following areas require more extensive research: 1. Increase the dose volume for solubility classification to 500 mL. 2. Include bile salt in the solubility measurement. 3. Use the intrinsic dissolution method for solubility classification. 4. Define an intermediate solubility class for BCS Class II drugs. 5. Include surfactants in in vitro dissolution testing.

Changes in the pharmacokinetics and electrocardiographic pharmacodynamics of terfenadine with concomitant administration of erythromycin

Terfenadine is a nonsedating H1‐antagonist that when overdosed, used with hepatic compromise, or when given with ketoconazole results in accumulation of parent terfenadine, prolongation of the QT interval, and torsades de pointes in susceptible patients. Nine subjects were given the recommended dose of terfenadine (60 mg every 12 hours) for 7 days before initiation of oral erythromycin (500 mg every 8 hours). All subjects increased metabolite concentrations after the addition of erythromycin for 1 week. The maximum concentration of metabolite increased by a mean of 107% and the mean metabolite area under the concentration‐time curve increased by 170%. Three subjects accumulated unmetabolized terfenadine after administration of erythromycin for 1 week. Electrocardiographic data revealed changes in QT intervals and ST‐U complexes in a subset of subjects who accumulated terfenadine. We conclude that erythromycin alters the metabolism of terfenadine, leading to accumulation of terfenadine in certain individuals that is associated with altered cardiac repolarization.

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 (Cmax) and area under the plasma drug concentration versus time curve (AUC), representing drug rate and extent of absorption, respectively. The generic/innovator Cmax 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 Cmax and AUC. Results: The mean ± SD of the GMRs from the 2070 studies was 1.00 ± 0.06 for Cmax and 1.00 ± 0.04 for AUC. The average difference in Cmax 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 FDAs objective of approving generic drug formulations that are therapeutically equivalent to their innovator counterparts.

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.

Bioavailability and bioequivalence: an FDA regulatory overview.

Bioavailability and/or bioequivalence studies play a key role in the drug development period for both new drug products and their generic equivalents. For both, these studies are also important in the postapproval period in the presence of certain manufacturing changes. Like many regulatory studies, the assessment of bioavailability and bioequivalence can generally be achieved by considering the following three questions. What is the primary question of the study? What are the tests that can be used to address the question? What degree of confidence is needed for the test outcome? This article reviews the regulatory science of bioavailability and bioequivalence and provides FDAs recommendations for drug sponsors who intend to establish bioavailability and/or demonstrate bioequivalence for their pharmaceutical products during the developmental process or after approval.

Dissolution testing for generic drugs: an FDA perspective.

In vitro dissolution testing is an important tool used for development and approval of generic dosage forms. The objective of this article is to summarize how dissolution testing is used for the approval of safe and effective generic drug products in the United States (US). Dissolution testing is routinely used for stability and quality control purposes for both oral and non-oral dosage forms. The dissolution method should be developed using an appropriate validated method depending on the dosage form. There are several ways in which dissolution testing plays a pivotal role in regulatory decision-making. It may be used to waive in vivo bioequivalence (BE) study requirements, as BE documentation for Scale Up and Post Approval Changes (SUPAC), and to predict the potential for a modified-release (MR) drug product to dose-dump if co-administered with alcoholic beverages. Thus, in vitro dissolution testing plays a major role in FDA’s efforts to reduce the regulatory burden and unnecessary human studies in generic drug development without sacrificing the quality of the drug products.

The effect of fluconazole on the steady-state pharmacokinetics and electrocardiographic pharmacodynamics of terfenadine in humans.

Terfenadine is rapidly and nearly completely biotransformed during a first pass to an active acid metabolite. Accumulation of unmetabolized terfenadine has been associated with altered cardiac repolarization. Drug‐drug interactions resulting in the accumulation of terfenadine have been reported for ketoconazole and erythromycin. Six subjects were given the recommended dose of terfenadine (60 mg every 12 hours) for 7 days before initiation of oral fluconazole (200 mg once daily). The mean metabolite area under the concentration‐time curve increased by 34% and the time to maximum concentration of the metabolite was delayed from 2.3 to 4 hours by concurrent fluconazole. Unmetabolized terfenadine was not present in any subject, and cardiac repolarization was not significantly changed from baseline during any phase of the study. We conclude that a pharmacokinetic interaction between terfenadine and fluconazole exists; however, the absence of accumulation of parent terfenadine in plasma suggests that a clinically significant interaction is unlikely.

Highly Variable Drugs: Observations from Bioequivalence Data Submitted to the FDA for New Generic Drug Applications

IntroductionIt 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 MethodsWe 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 Cmax and/or AUC was ≥0.3. To identify factors contributing to high variability, we evaluated drug substance pharmacokinetic characteristics and drug product dissolution performance.Results and DiscussionIn 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.ConclusionAbout 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.

Evaluation of a Scaling Approach for the Bioequivalence of Highly Variable Drugs

Various approaches for evaluating the bioequivalence (BE) of highly variable drugs (CV ≥ 30%) have been debated for many years. More recently, the FDA conducted research to evaluate one such approach: scaled average BE. A main objective of this study was to determine the impact of scaled average BE on study power, and compare it to the method commonly applied currently (average BE). Three-sequence, three period, two treatment partially replicated cross-over BE studies were simulated in S-Plus. Average BE criteria, using 80–125% limits on the 90% confidence intervals for Cmax and AUC geometric mean ratios, as well as scaled average BE were applied to the results. The percent of studies passing BE was determined under different conditions. Variables tested included within subject variability, point estimate constraint, and different values for σw0, which is a constant set by the regulatory agency. The simulation results demonstrated higher study power with scaled average BE, compared to average BE, as within subject variability increased. At 60% CV, study power was more than 90% for scaled average BE, compared with about 22% for average BE. A σw0 value of 0.25 appears to work best. The results of this research project suggest that scaled average BE, using a partial replicate design, is a good approach for the evaluation of BE of highly variable drugs.

FDA Evaluations Using In Vitro Metabolism to Predict and Interpret In Vivo Metabolic Drug‐Drug Interactions: Impact on Labeling

Recent advances in in vitro metabolism methods have led to an improved ability to predict clinically relevant metabolic drug‐drug interactions. To address the relationships of in vitro metabolism data and in vivo metabolism outcomes, the Office of Clinical Pharmacology and Biopharmaceutics in the Center for Drug Evaluation and Research, Food and Drug Administration, evaluated a number of recently approved new drug applications. The goal of these evaluations was to determine the contribution of in vitro metabolism data in (1) predicting in vivo drug‐drug interactions, (2) determining the need to conduct an in vivo drug‐drug interaction study, and (3) incorporating findings into drug product labeling. Ten cases are presented in this article. They fall into two major groups: (1) in vitro data were predictive of in vivo results, and (2) in vitro data were not predictive of in vivo results. Discussion of these cases highlights factors limiting predictability of in vivo metabolic interactions from in vitro metabolism data. The integration of these findings into drug product labeling is also discussed.