Methoden vergelijken
Bekijk de geselecteerde methoden naast elkaar; rijen die verschillen zijn gemarkeerd.
| Emax-model: Farmacodynamische dosis-responsanalyse× | Experimenteel ontwerp en analyse van dosis-responsrelaties× | |
|---|---|---|
| Vakgebied≠ | Farmacometrie | Experimenteel ontwerp |
| Familie≠ | Regression model | Hypothesis test |
| Jaar van ontstaan≠ | 1981 | 1994 |
| Grondlegger≠ | Holford & Sheiner | Classical pharmacology; formalized by ICH E4 (1994) and Ritz et al. (2015) |
| Type≠ | Nonlinear dose-response regression model | Nonlinear curve fitting and monotone contrast testing |
| Oorspronkelijke bron≠ | 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. DOI ↗ | Ritz, C., Baty, F., Streibig, J. C., & Gerhard, D. (2015). Dose-Response Analysis Using R. PLOS ONE, 10(12), e0146021. DOI ↗ |
| Aliassen≠ | 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 |
| Verwant≠ | 2 | 4 |
| Samenvatting≠ | 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. |
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