Abstract
Average bioequivalence is used to assess pharmacokinetic properties of proposed generic drug before they are marketed. The limitations of average bioequivalence have led the U.S. Food and Drug Administration to propose the use of popUlation bioequivalence and individual bioequivalence. In this study, bootstrap confidence intervals were used to evaluate population bioequivalence and individual bioequivalence in the context of a 2 x 4 crossover experimental design. Two bioequivalence criteria were compared: the mean-squared difference criterion and a probability-based criterion. Simulations were conducted to study the properties of the bootstrap confidence intervals under each criterion in establishing population bioequivalence or individual bioequivalence. Various inter-subject, within-subject, and subject-by-formulation interaction variance components were considered.
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Recommended Citation
Yu, Feng; Young, Linda J.; and Stevens, Gary R.
(2000).
"ESTABLISHING POPULATION AND INDIVIDUAL BIOEQUIVALENCE CONFIDENCE INTERVALS,"
Conference on Applied Statistics in Agriculture.
https://doi.org/10.4148/2475-7772.1242
ESTABLISHING POPULATION AND INDIVIDUAL BIOEQUIVALENCE CONFIDENCE INTERVALS
Average bioequivalence is used to assess pharmacokinetic properties of proposed generic drug before they are marketed. The limitations of average bioequivalence have led the U.S. Food and Drug Administration to propose the use of popUlation bioequivalence and individual bioequivalence. In this study, bootstrap confidence intervals were used to evaluate population bioequivalence and individual bioequivalence in the context of a 2 x 4 crossover experimental design. Two bioequivalence criteria were compared: the mean-squared difference criterion and a probability-based criterion. Simulations were conducted to study the properties of the bootstrap confidence intervals under each criterion in establishing population bioequivalence or individual bioequivalence. Various inter-subject, within-subject, and subject-by-formulation interaction variance components were considered.
