Vertaile menetelmiä

	Bioekvivalenssianalyysi (Kaksi yksisuuntaista testiä)	Emax-malli: Farmakodynaaminen annos-vastesuhteen analyysi
Tieteenala	Farmakometria	Farmakometria
Menetelmäperhe	Hypothesis test	Regression model
Syntyvuosi	1987	1981
Kehittäjä	Donald J. Schuirmann	Holford & Sheiner
Tyyppi	Parametric equivalence test	Nonlinear dose-response regression model
Alkuperäislähde	Schuirmann, D. J. (1987). A comparison of the two one-sided tests procedure and the power approach for assessing the equivalence of average bioavailability. Journal of Pharmacokinetics and Biopharmaceutics, 15(6), 657–680.	Holford, N. H. G., & Sheiner, L. B. (1981). Understanding the dose-effect relationship: clinical application of pharmacokinetic-pharmacodynamic models. Clinical Pharmacokinetics, 6(6), 429–453.
Rinnakkaisnimet	TOST Procedure, Average Bioequivalence, BE Analysis, Biyoeşdeğerlik Analizi	Maximum Effect Model, Hyperbolic Emax Model, Sigmoidal Emax Model, Emax Farmakodynamik Modeli
Liittyvät	2	2
Tiivistelmä	Bioequivalence Analysis is a regulatory-grade statistical framework used to determine whether a test drug formulation (generic or reformulated) delivers the active ingredient to the systemic circulation at a rate and extent comparable to a reference product. Introduced by Donald J. Schuirmann in 1987, the method operationalizes equivalence through the Two One-Sided Tests (TOST) procedure, replacing the ambiguous absence-of-difference paradigm with an explicit equivalence margin evaluated on log-transformed pharmacokinetic endpoints such as AUC and C_max.	The Emax model is a nonlinear pharmacodynamic model that describes the relationship between drug concentration and biological effect. Introduced by Holford and Sheiner in 1981, it characterizes dose-response curves using three fundamental parameters: the maximum achievable effect (Emax), the concentration producing half-maximal effect (EC50), and an optional baseline effect (E0). It remains the standard framework in clinical pharmacology and drug development for quantifying pharmacodynamic dose-response relationships.