方法对比

	Emax模型：药效剂量-效应分析	剂量-反应实验设计与分析	药代动力学房室模型
领域	定量药理学	实验设计	定量药理学
方法族	Regression model	Hypothesis test	Regression model
起源年份	1981	1994	1982
提出者	Holford & Sheiner	Classical pharmacology; formalized by ICH E4 (1994) and Ritz et al. (2015)	Gibaldi & Perrier
类型	Nonlinear dose-response regression model	Nonlinear curve fitting and monotone contrast testing	Deterministic ODE-based pharmacokinetic model
开创性文献	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.	Ritz, C., Baty, F., Streibig, J. C., & Gerhard, D. (2015). Dose-Response Analysis Using R. PLOS ONE, 10(12), e0146021.	Gibaldi, M., & Perrier, D. (1982). Pharmacokinetics (2nd ed.). Marcel Dekker. ISBN: 978-0-8247-1042-2
别名	Maximum Effect Model, Hyperbolic Emax Model, Sigmoidal Emax Model, Emax Farmakodynamik Modeli	dose-response analysis, dose-response curve, Doz-Yanıt Tasarımı ve Analizi (Dose-Response), ED50 analysis	Mammillary Compartment Model, Multi-Compartment PK Model, Compartmental Analysis, Farmakokinetik Kompartman Modeli
相关	2	4	3
摘要	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.	Dose-response design is a framework for planning and analysing experiments that characterise the relationship between the amount of a stimulus — such as a drug dose or a chemical concentration — and the magnitude of a biological or physiological response. Formalised in regulatory guidance by the ICH E4 guideline (1994) and extensively developed in the statistical literature by Ritz et al. (2015), the framework covers experiment design, four-parameter and five-parameter logistic curve fitting, key benchmark estimates (ED50/EC50, NOAEL, LOAEL), and monotone trend testing via the Williams procedure.	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.