Comparer des méthodes

	Modèle compartimental pharmacocinétique	Modèle Emax : Analyse pharmacodynamique dose-réponse	Pharmacocinétique de population
Domaine	Pharmacométrie	Pharmacométrie	Pharmacométrie
Famille	Regression model	Regression model	Regression model
Année d'origine	1982	1981	1977
Auteur d'origine	Gibaldi & Perrier	Holford & Sheiner	Sheiner, Rosenberg & Marathe
Type	Deterministic ODE-based pharmacokinetic model	Nonlinear dose-response regression model	Nonlinear mixed-effects regression model
Source fondatrice	Gibaldi, M., & Perrier, D. (1982). Pharmacokinetics (2nd ed.). Marcel Dekker. ISBN: 978-0-8247-1042-2	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.	Sheiner, L. B., Rosenberg, B., & Marathe, V. V. (1977). Estimation of population characteristics of pharmacokinetic parameters from routine clinical data. Journal of Pharmacokinetics and Biopharmaceutics, 5(5), 445–479.
Alias	Mammillary Compartment Model, Multi-Compartment PK Model, Compartmental Analysis, Farmakokinetik Kompartman Modeli	Maximum Effect Model, Hyperbolic Emax Model, Sigmoidal Emax Model, Emax Farmakodynamik Modeli	PopPK, Nonlinear Mixed-Effects Modeling, NONMEM Approach, Popülasyon Farmakokinetiği
Apparentées	3	2	2
Résumé	The pharmacokinetic compartment model represents the body as one or more hypothetical compartments interconnected by first-order rate processes, describing how a drug is absorbed, distributed, and eliminated over time. Systematized by Gibaldi and Perrier in 1982, these models use ordinary differential equations to characterize plasma concentration-time profiles. They are the cornerstone of drug development, dosage regimen design, and regulatory submission pharmacokinetic analyses.	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.	Population Pharmacokinetics (PopPK) is a nonlinear mixed-effects modeling framework that characterizes how drugs are absorbed, distributed, metabolized, and eliminated across a patient population, estimating both typical population parameters and the magnitude of between-subject variability. Introduced by Sheiner, Rosenberg, and Marathe in 1977, it enables parameter estimation from sparse, routinely collected clinical data—making it indispensable in drug development, regulatory submissions, and individualized dosing.