title: Non-traditional study designs to demonstrate average bioequivalence for highly variable drug products.
abstract: OBJECTIVE
  To demonstrate average bioequivalence, the ninety-percent confidence intervals (CI) on the ratio of geometric means for area under the concentration-time curve (AUC) and maximum observed plasma concentration (Cmax) must lie within 0.80-1.25. Demonstration of average bioequivalence (ABE) for highly variable drug products requires large numbers of subjects in a standard, adequately powered, two-period crossover.
  
  
  METHODS
  Application of non-traditional study designs can help to meet this hurdle. Study design and analysis for replicate and group sequential-replicate study designs are presented and illustrated using examples. It is demonstrated how to use such approaches to meet the difficult regulatory hurdle of average bioequivalence for a highly variable drug product.
  
  
  RESULTS
  To illustrate, data are provided from three separate ABE studies for a highly variable drug product at three dosage strengths. In all three studies, a replicate study design was used to compensate for high intrasubject variation. Additionally, for the last study, a group sequential study design was imposed to provide early evidence of conclusive results.
  
  
  CONCLUSIONS
  Replicate designs and group-sequential designs in bioequivalence should be used to demonstrate average bioequivalence for highly variable drug products or when uncertain of true intrasubject variability in order to ensure conclusive study results.
authors.affiliation: GlaxoSmithKline Pharmaceuticals, Collegeville, PA 19426-0989, USA. scott_d_patterson@gsk.com
authors.forename: S D
authors.initials: SD
authors.lastname: Patterson
authors.forename: N M
authors.initials: NM
authors.lastname: Zariffa
authors.forename: T H
authors.initials: TH
authors.lastname: Montague
authors.forename: K
authors.initials: K
authors.lastname: Howland
mesh_terms: D019540:Area Under Curve; D018592:Cross-Over Studies; D006801:Humans; D015233:Models, Statistical; D012107:Research Design; D013810:Therapeutic Equivalency