• Journal of Pharmaceutical Investigation
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• v.28 no.4
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• pp.231-239
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• 1998

A $3{\times}2$ crossover design is considered for the bioequivalence of two test formulations with a control. It could be considered as a better choice over $3{\times}3$ crossover design because of the cost and experimental duration. Oh et al.(1998) derived $3{\times}2$ crossover design and discussed its benefits over the typical crossover designs. We consider here the statistical models for $3{\times}2$ crossover design and show its statistical properties. The statistical procedures for the bioequivalence in $3{\times}2$ crossover design are shown through an example and the results are summarized by satisfying the 3 standards that proposed by the Korea Food and Drug Administration Guidelines for Bioequivalence.

• Communications for Statistical Applications and Methods
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• v.27 no.6
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• pp.641-647
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• 2020

The 2 × 3 crossover design, a modified version of the 3 × 3 crossover design, is considered to compare the bioavailability of two generic candidates with a reference drug. The 2 × 3 crossover design is more economically favorable due to decrease in the number of sequences, rather than conducting a 3×3 crossover trial or two separate 2 × 2 crossover trials. However, when using a higher-order crossover trial, the risk of drop-outs and withdrawals of subjects increases, so the suitable statistical inferences for missing data is needed. The bioequivalence model of a of 2×3 crossover trial with missing data is defined and the statistical procedures of assessing bioequivalence is proposed. An illustrated example of the 2 × 3 trial with missing data is also presented with discussion.

• 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 Statistical Society
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• v.29 no.2
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• pp.219-229
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• 2000

Oh et al.(1999) 3$\times$2 crossover design for assessing bioequivalence when two new generic drug formulations and innovator are simultaneously considered. This design is not only more efficient than 3$\times$3 one, proposed by Lee et al.(1998), in practical sense, but also more ethical in medical sense. However, the general statistical methods are not directly applicable to both designs when subjects are dropped out in the experiment, even though it is always possible in bioavailability and bioequivalence studies because of some administrative and economic reasons. In this research we propose an inference to drug effects when subjects are dropped out in the planed-for 3$\times$3 and 3$\times$2 crossover experiments. An example is given for illustration.

• 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.

• 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.

• 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.

• Journal of the Korean Statistical Society
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• v.35 no.3
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• pp.239-250
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• 2006

A $2{\times}2$ crossover design including carryover effect is considered for assessment of population bioequivalence of two drug formulations in a Bayesian framework. In classical analysis, it is complex to deal with the carryover effect since the estimate of the drug effect is biased in the presence of a carryover effect. The proposed method in this article uses uninformative priors and vague proper priors for objectiveness of priors and the posterior probability distribution of the parameters of interest is derived with given priors. The posterior probabilities of the hypotheses for assessing population bioequivalence are evaluated based on a Markov chain Monte Carlo simulation method. An example with real data set is given for illustration.

• YAKHAK HOEJI
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• v.39 no.4
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• pp.401-410
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• 1995

Pharmacolinetic profiles of omeprazole enteric coated granules including Ramezole$^\circledR$, Losec$^\circledR$, omeprazole-Na and omeprazole-resin salt were studied using the crossover design in rats and rabbits. The absorption variance of the preparations at the altered pH condition of the gastrointestinal tract was also studied. After oral administration of four omeprazole enteric coated pellets (10mg/kg) with and without concomitant administration NaHCO$_{3}$ (5 mg/ml, 60 mM) in the rats, the differences of absorplion rate and extent were evaluated. In the NaHCO$_{3}$, administration group, the T$_{max}$ appeared to be 2~10 times shorter than water administration group, and the $C_{max}$ also increased to about 4 times, and the AUC increased to about 2.5 times. Pharmacokinetic parameters of four omeprazole enteric coated pellets in rats showed no statistical significance (ANOVA, P>0.05) in both groups. In the crossover study, the second dosed drug showed 4~5 times increased bioavailability than first dosed drug, which shows the strong carry-over effect of acid secretion of the first dosed drug. The differences of the pharmacokinetic parameters of the two test formulations (Losec$^\circledR$ and omeprazole-resin) showed no statistical significance.

• Journal of the Korean Data and Information Science Society
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• v.18 no.3
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• pp.645-657
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• 2007

Several statistical procedures for assessment of bioequivalence of variabilities between two drug formulations in bioequivalence trials are reviewed and modified methods for assessing total variability are suggested. The problem of the current US FDA aggregate criterion for population bioequivalence and the necessity of disaggregate criterion are discussed with an illustrated example.