title: Regulatory and study conditions for the determination of bioequivalence of highly variable drugs.
abstract: OBJECTIVE
  The FDA Working Group on Highly Variable (HV) Drugs recently presented interim procedures and conditions for determining the bioequivalence (BE) of HV drug products. They included analysis by the method of scaled average BE (SABE), a switching coefficient of variation of CV S = 30% and a regulatory standardized variation of CV 0 = 25% for applying SABE, and the use of a secondary regulatory criterion restricting to 0.80-1.25 the point estimate for the ratio of estimated geometric means (GMR) of the two formulations. These conditions are scrutinized in the present communication.
  
  
  METHODS
  3-period BE studies were simulated with various statistical and regulatory assumptions. Power curves, obtained by gradually increasing the true GMR, compared performances of the methods of SABE, a constrained point estimate of GMR (PE/GMR), and the composite of these two approaches. The consumer risk of each procedure was evaluated.
  
  
  RESULTS
  With CV 0 = 30% and PE/GMR = 0.80-1.25, the composite criterion of BE relied on the confidence limits of SABE. In contrast, with CV 0 = 25% and/or PE/GMR = 0.87-1.15, the composite criterion approached almost completely the features of the GMR point estimate, especially at high within-subject variation. The consumer risk was near 5% with CV 0 = 30% but much higher when CV 0 = 25%.
  
  
  CONCLUSIONS
  A constraint on GMR is difficult to justify scientifically. Still, if it is introduced then the condition of CV S = CV 0 = 30% and PE/GMR = 0.80-1.25 is recommended as a composite regulatory criterion. With alternative settings of the conditions, such as the recommended CV 0 = 25% and/or PE/GMR = 0.87-1.15, the composite criterion would reflect almost entirely the GMR point estimate. Also, with CV 0 = 25%, the BE limits are discontinuous at CVS = 30% and, as consequences, the consumer risk is substantially larger than 5%, and the regulatory uncertainty for making a decision about acceptance or rejection is enhanced. These would be undesirable outcomes.
authors.affiliation: University of Toronto, Department of Pharmacology, Toronto, Ontario, Canada. l.endrenyi@utoronto.ca
authors.forename: Laszlo
authors.initials: L
authors.lastname: Endrenyi
authors.forename: Laszlo
authors.initials: L
authors.lastname: Tothfalusi
mesh_terms: D000465:Algorithms; D019540:Area Under Curve; D002626:Chemistry, Pharmaceutical; D015233:Models, Statistical; D004364:Pharmaceutical Preparations / Q000737:chemistry*; D010599:Pharmacokinetics; D012015:Reference Standards; D012016:Reference Values; D013678:Technology, Pharmaceutical / Q000379:methods*; D013810:Therapeutic Equivalency
chemical_list: D004364:Pharmaceutical Preparations