DOI QR코드

DOI QR Code

Assessing bioequivalence in 2×3 dual designs

2×3 이중 설계에서 생물학적 동등성 평가

  • Woo, Hwa Hyoung (Department of Applied Statistics, Chung-Ang University) ;
  • Jeong, Gyu Jin (Department of Business Statistics, Han Nam University) ;
  • Park, Sang-Gue (Department of Applied Statistics, Chung-Ang University)
  • 우화형 (중앙대학교 응용통계학과) ;
  • 정규진 (한남대학교 비즈니스통계학과) ;
  • 박상규 (중앙대학교 응용통계학과)
  • Received : 2017.06.08
  • Accepted : 2017.07.08
  • Published : 2017.07.31

Abstract

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.

두 제제의 생체이용률을 비교하여 동등성을 입증하는 생물학적 동등성 시험은 표준 $2{\times}2$ 교차설계를 원칙으로 하고 있으나, 최근에는 제제의 특성이 고변동성으로 인해 표준 $2{\times}2$ 교차설계를 사용할 경우 지나치게 많은 피험자가 필요하게 되면서, EMA나 MFDS 등에서는 $2{\times}2$ 교차설계를 확장한 $2{\times}4$, $4{\times}2$ 또는 $4{\times}4$ 등의 고차원 설계를 권장하고 있다. $2{\times}3$ 교차설계는 표준 $2{\times}2$ 교차설계에서 1기간을 확장한 설계로 불균형 설계이기는 하지만 $2{\times}4$ 교차설계와 비교해서 경제적, 윤리적 측면에서 장점을 갖고 있는 설계라 할 수 있다. 본 연구에서는 $2{\times}3$ 이중설계를 활용하는 생물학적 동등성 시험에서 설계의 통계적 특성을 고찰해 보고, 생물학적 동등성 평가를 위한 통계적 설계 및 추론 절차를 새롭게 개정된 의약품동등성시험기준을 적용하여 논의한다.

Keywords

References

  1. Chow, S. C. and Liu, L. (2008). Design and analysis of bioavailability and bioequivalence studies, Chapman & Hall.
  2. Chow, S. C., Shao, J. and Wang, H. (2002). Individual bioequivalence testing under $2{\times}3$ designs. Statistics in Medicine, 21, 629-648. https://doi.org/10.1002/sim.1056
  3. Chow, S. C. and Wang, H. (2001). On sample size calculation in bioequivalence trials. Journal of Pharmacokinetics and Pharmacodynamics, 28, 155-169. https://doi.org/10.1023/A:1011503032353
  4. EMA (2010). MEA guideline on the investigation of bioequivalence, CPMP/EWP/QWP/1401/98 Rev.1/Corr, London.
  5. Jeong, G. and Park, S. (2011). On evaluation of bioequivalence for highly variable drugs. Korean Journal of Applied Statistics, 24, 1055-1076. https://doi.org/10.5351/KJAS.2011.24.6.1055
  6. Kershner R. P. and Federer, W. T. (1981). Two-treatment crossover designs for estimating a variety of effects. Journal of the American Statistical Association, 76, 612-618. https://doi.org/10.1080/01621459.1981.10477693
  7. Noh, S. and Park, S. (2013). Some statistical consideration on $2{\times}k$ crossover designs for bioequivalence trial. Korean Journal of Applied Statistics, 26, 675-686. https://doi.org/10.5351/KJAS.2013.26.4.675
  8. Park, J. and Park, S. (2016). Assessing bioequivalence for highly variable drugs based on $3{\times}3$ crossover designs. Korean Journal of Applied Statistics, 29, 279-289. https://doi.org/10.5351/KJAS.2016.29.2.279
  9. Park, S. (2007). On sample size determination of bioequivalence trials. Journal of Korean Data & Information Science Society, 18, 365-373.
  10. Woo, H. and Park, S. (2014). Statistical procedures of add-on trials for bioequivalence in $2{\times}k$ crossover designs. Journal of Korean Data & Information Science Society, 25, 1181-1193. https://doi.org/10.7465/jkdi.2014.25.6.1181