• The Korean Journal of Applied Statistics
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• v.15 no.2
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• pp.281-296
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• 2002

On the new medical system separating the prescription and dispensing of the drug, the qualification of pharmacist in substitution of prescribed medicine was restricted, except bioequivalence-certified drugs. Also, Korean Food and Drug Association(KFDA) revised the bioequivalence regulation on August, 2001 Among many changes from old guideline, impressive one is the statistical consideration. Specially, to estimate and analyze bioequivalence measures, AUC and $C_{max}$, the log-transformed model is recommended and the equivalence interval is modified from $\pm$20 rule to [In(0.8),In(1.25)] one. This meaningful act is very hope-for because it is statistically reasonable and is agreed with worldwide bioequivalence guideline, including USA, EU, Japan and Canada. In this paper, we introduce the new regulation of assessing bioequivalence, announced at August, 2001, mainly on statistical view points. Key points for the new regulation are discussed and the minimum sample size based on simulation studies are proposed.

• The Korean Journal of Applied Statistics
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• v.23 no.1
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• pp.139-150
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• 2010

In recent years, more generic drug products became available. The current regulation for assessing the bioequivalence of two drug formulations is based on the concept of average bioequivalence. This approach has been indicated to be insufficient for assessing switchability between two drug formulations and US FDA has adopted individual bioequivalence as one of the bioequivalence criterion since 2001. The US FDA recommends that individual bioequivalence be assessed based on $2\;{\times}\;4$ crossover design, while a $2\;{\times}\;3$ crossover design may be used as an alternative design to reduce the length and cost of the study. In this paper, a statistical procedure for assessment of individual bioequivalence under $3\;{\times}\;2$ crossover designs is proposed and some statistical points are discussed with $2\;{\times}\;3$ crossover design and $2\;{\times}\;3$ extra-reference design through simulation studies.

• The Korean Journal of Applied Statistics
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• v.26 no.4
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• pp.675-686
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• 2013

The Korea Food and Drug Administration(KFDA) recommends the use of a $2{\times}2$ crossover design to assess the bioequivalence of generic drugs. However, a standard $2{\times}2$ crossover design for bioequivalence trials is often considered problematic due to ethical and economic issues as highly variable drugs are usually required by large numbers of subjects when designing the trial. To overcome this problem a $2{\times}4$ crossover design has been a recommended option as per US regulations; in addition, a $2{\times}3$ crossover design has also recently drawn special attention as an efficient alternative. The current KFDA regulation requires an ANOVA table for every bioequivalence study; however, ANOVA tables of $2{\times}4$ and $2{\times}3$ crossover designs have never been published in the literature. This study shows the derivation of tables of analysis of variance for a $2{\times}4$ cross-over design and a $2{\times}3$ cross-over design. We also suggest a sample size formulas for $2{\times}2$, $2{\times}4$ and $2{\times}3$ crossover designs to provide information on the selection of efficient designs for highly variable drugs.