An individual bioequivalence criterion: regulatory considerations

Abstract

Over the years, concerns have been raised regarding the appropriateness of using the average bioequivalence approach for evaluation of comparability between formulations. In lieu of average bioequivalence, scientists from academia, industry and regulatory agencies have spent considerable effort and time in exploring the concepts of population and individual bioequivalence, and developing the statistical methods to assess the bioavailability metrics using these approaches. Recently, the Food and Drug Administration (FDA) has published a preliminary draft guidance entitled 'In vivo bioequivalence studies based on population and individual bioequivalence approaches'. The concept of prescribability and switchability underscores the difference between the population and individual bioequivalence approaches. The most important consideration for individual bioequivalence, the focus of this paper, rests on the assurance that products deemed bioequivalent can be used interchangeably in the target population (switchability). In addition to the comparison of averages, the individual bioequivalence approach compares within-subject variabilities and assesses subject-by-formulation interaction. The proposed criterion represents substantial departure from the current practice and thus has resulted in extensive public discussion. In contrast to the current average bioequivalence procedure, the proposed individual bioequivalence approach offers flexible equivalence criteria based on the individual therapeutic window and variability of the reference drug product. The proposed criterion rewards manufacture of less variable drug products, allows scaling criteria for highly variable/narrow therapeutic range drugs, and promotes the use of subjects from the general population in bioequivalence studies. The FDA is currently considering various approaches for resolution of issues raised from the public debate on the subject-by-formulation interaction term, statistical methods and resource implications.