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Consideration of individual bioequivalence

  • Sharon Anderson
  • Walter W. Hauck
Pharmacometrics

Abstract

Current procedures for assessing the bioequivatence of two formulations are based on the concept of average bioequivalence. That is, they assess whether the average responses between individuals on the two formulations are similar. Average bioequivalence, however, is not sufficient to guarantee that an individual patient could be expected to respond similarly to the two formulations. To have reasonable assurance that an individual patient could be switched from a therapeutically successful formulation to a different formulation (e.g., a generic substitute) requires a different notion of bioequivalence, which we refer to as individual (or within-subject) bioequivalence. We propose a simple, valid statistical procedure for assessing individual bioequivalence. The decision rule, TIER (Test of Individual Equivalence Ratios), requires the specification of the minimum proportion of subjects in the applicable population for which the two formulations being tested must be bioequivalent (a regulatory decision). The TIER rule is summarized in terms of the minimum number of subjects with bioavailability ratios falling within the specified equivalence interval necessary to be able to claim bioequivalence for given sample size and Type I (α) error. We recommend that the corresponding lower bounds (one-sided confidence intervals) for the proportion of bioequivalent subjects be calculated. TIER is partly motivated by the U.S. FDA's 75/75 Rule (at least 75% of the individual subject bioavailability ratios must be within 75–125%). TIER retains the sensible idea of considering the individual ratios but, unlike the 75/75 rule, is a statistically valid procedure.

Key words

bioequivalence binomial tests 75/75 rule 

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Copyright information

© Plenum Publishing Corporation 1990

Authors and Affiliations

  • Sharon Anderson
    • 1
    • 2
  • Walter W. Hauck
    • 2
  1. 1.Syntex ResearchPalo Alto
  2. 2.Department of Epidemiology and BiostatisticsUniversity of CaliforniaSan Francisco

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