| Title | Bioequivalence trials: procedures and regulations for testing, measuring and analyzing critical biochemical factors for the purpose of providing effective, efficient and safe alternative drugs in medical practice | |
| Author | Elisavet-Adamantia G. Masourou
2nd Internal Medicine Clinic, Henry Dunant Hospital, Red Cross Foundation, 107 Mesogion Avenue, GR-11528 Athens, Greece |
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| Citation | Masourou, E.-A.,G.: Bioequivalence trials: procedures and regulations for testing, measuring and analyzing critical biochemical factors for the purpose of providing effective, efficient and safe alternative drugs in medical practice, Epitheorese Klin. Farmakol. Farmakokinet. 25(2): 83-90 (2011) | |
| Publication Date | Accepted for publication (Final version): July 1, 2011 | |
| Full Text Language | English | |
| Order – Buy | Ηλεκτρονική Μορφή: pdf (10 €) – Digital Type: pdf (10 €)
pharmakonpress[at]pharmakonpress[.]gr |
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| Keywords | Bioequivalence studies, comparative bioavailability, statistical analysis, crossover design, the null hypothesis, type I and type II statistical errors, statistical power – sensitivity. | |
| Other Terms | review article | |
| Summary | This is an introductory survey paper dealing with the statistical analysis of the bioavailability factors (peak plasma concentration Cmax, time to reach this concentration Tmax and the Area Under Concentration-time curve AUC), which determine the Bioequivalence of generic drugs. Issues, like the selection of the proper representative sample and the crossover versus parallel longitudinal study, are discussed. The different phases of the data analysis are presented and the pure mathematical tools, such as null hypothesis, the types of errors, are approached comprehensively, with proper examples. Through the theoretical analysis, it becomes obvious that the manufacturer’s risk rises as the consumer’s risk is kept small. It is explained through real-life examples that it is not feasible to set international statistical standards regarding the acceptable limits of Type I and Type II errors, as the essence of these errors changes significantly, in a case by case basis. Nevertheless, the absence of such standards makes the existence of the regulatory organizations evident. According to regulations applicable in the European Union, the bioequivalence of two medicinal products is considered demonstrated if the 90% confidence intervals (90% CI) of the ratios for AUC0-t and Cmax between the two preparations lie in the range 80.00-125.00%. The FDA considers two products bioequivalent if the 90% CI of the relative mean Cmax, AUC(0-t) and AUC(0-∞) of the test (e.g. generic formulation) to reference (e.g. innovator brand formulation) belong in the interval 80.00% to 125.00% in the fasting state. | |
| References | 1. Wikipedia, the free encyclopedia
2. Center for Drug Evaluation and Research: Guidance for Industry: Bioavailability and Bioequivalence Studies for Orally Administered Drug Products: General Considerations. United States Food and Drug Administration, 2003 3. Committee for Medicinal Products for Human Use: Guideline on the Investigation of Bioequivalence. European Medicines Agency, (20 January 2010. Retrieved 21 April 2011. 4. Najafi Mehdi (ed.): Statistical Questions in Evidence Based Medicine. Oxford University Press, New York, 2004; ISBN 0-19-262992-1 5. Jones Byron, Kenward Michael G. (eds): Design and Analysis of Cross-Over Trials. Second ed., Chapman and Hall, London, 2003 6. Stufken J.: Optimal Crossover Designs. In: (Ghosh S., Rao C.R., eds) Design and Analysis of Experiments. Handbook of Statistics, pp. 63-90, North-Holland, 1996, ISBN 0-444-82061-2 7. Vonesh Edward F., Chinchilli Vernon G.: Crossover Experiments. Linear and Nonlinear Models for the Analysis of Repeated Measurements. Pp. 111-202, Chapman and Hall, London, 1997 8. Cohen J.: Statistical Power Analysis for the Behavioral Sciences. 2nd ed., 1988; ISBN 0-8058-0283-5. 9. Aberson C.L.: Applied Power Analysis for the Behavioral Science. 2010. ISBN 1-8487-2835-2. 10. Popović J., Mikov M., Sabo A., Jakovljević V.: Evaluation of statistical power function for various diclofenac bioequivalence trials with different subject numbers. Eur. J. Drug Metab. Pharmacokinet. 34: 85-91 (2009) 11. Wang H., Chow S.C.: On statistical power for average bioequivalence testing under replicated crossover designs. J. Biopharm. Stat. 12: 295-309 (2002) |
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