de.mpg.escidoc.pubman.appbase.FacesBean
Deutsch
 
Hilfe Wegweiser Impressum Kontakt Einloggen
  DetailsucheBrowse

Datensatz

DATENSATZ AKTIONENEXPORT

Freigegeben

Zeitschriftenartikel

Biometrical evaluation of bioequivalence trials using a bootstrap individual direct curve comparison method.

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons50393

Kowald,  Axel
Independent Junior Research Groups (OWL), Max Planck Institute for Molecular Genetics, Max Planck Society;

Externe Ressourcen
Es sind keine Externen Ressourcen verfügbar
Volltexte (frei zugänglich)
Es sind keine frei zugänglichen Volltexte verfügbar
Ergänzendes Material (frei zugänglich)
Es sind keine frei zugänglichen Ergänzenden Materialien verfügbar
Zitation

Zintzaras, E., Bouka, P., & Kowald, A. (2002). Biometrical evaluation of bioequivalence trials using a bootstrap individual direct curve comparison method. European Journal of Drug Metabolism and Pharmacokinetics, 27(1), 11-16.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0010-8CC6-F
Zusammenfassung
Bioequivalence of two medicinal, or veterinary, products is established by comparing the mean of bioavailability measures, such as AUC and Cmax, following administration of the test (T) and reference (R) products. However, the use of these parameters has several drawbacks, e.g. they do not take into consideration the overall pharmacokinetic profile shape. Therefore, concerns have been raised regarding their appropriateness for assessment of bioequivalence. To overcome the limitations of these bioequivalence parameters, direct curve comparison metrics methods were recently proposed on an average basis. In this paper, an individual based direct curve comparison method for assessing bioequivalence is proposed. The bioequivalence of T and R in each subject is evaluated by a new curve comparison metrics delta. The metrics delta is the absolute sum of the difference between two curves. The significance of the metrics for each subject is assessed by bootstrapping. An overall bioequivalence of T and R may be considered if less than 25% of the subjects show statistically different profiles.