• The Korean Journal of Applied Statistics
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• v.29 no.2
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• pp.279-289
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• 2016

Bioequivalence trials based on higher order crossover designs have recently been conducted for highly variable drugs since the Ministry of Korea Food and Drug Safety (MFDS) added new regulations in 2013 to widen bioequivalence limits for highly variable drugs. However, a statistical discussion of higher order crossover designs have not been discussed yet. This research proposes the statistical inference of bioequivalence based on $3{\times}3$ crossover design and discusses it with the MFDS regulations. An illustrated example is also given.

• Journal of the Korean Data and Information Science Society
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• v.25 no.6
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• pp.1181-1193
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• 2014

Currently Ministry of food and drug safety allows add-on trial when the bioequivalence between two drugs fails to show since July 1, 2008. However, bioequivalence of highly variable drugs based on $2{\times}2$ crossover designs would require too many subjects, so the alternative designs like $2{\times}4$ or $2{\times}3$ crossover experiments are preferred. In this paper, we propose and discuss the statistical procedures for add-on trials in $2{\times}4$ and $2{\times}3$ crossover designs.

• 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.

• Journal of the Korean Data and Information Science Society
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• v.28 no.4
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• pp.743-754
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• 2017

Assessing bioequivalence between original drug and generic drug is traditionally based on $2{\times}2$ crossover design. As bioequivalence trials for highly variable drugs are getting popular, the required sample size based on $2{\times}2$ crossover design would be very large, which might cause the ethical concerns. Regulatory agencies like EMA and MFDS recommended higher order crossover designs such as $2{\times}4$, $4{\times}2$ and $4{\times}4$ crossover designs. Alternatively, a $2{\times}3$ dual design may be recommended in terms of economical and ethical points of view in comparison with the $2{\times}4$ crossover design for highly variable drug. In this study, we consider some statistical characteristics of $2{\times}3$ dual design and propose statistical procedures for calculating sample size and assessing bioequivalence based on $2{\times}3$ dual design. We also discuss the proposed procedures from the perspective of newly revised bioequivalence guidance issued by MFDS.