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Kinetyka Michaelisa-Menten×Modelowanie farmakodynamiczne populacyjne×Analiza Schild×
DziedzinaFarmakologiaFarmakologiaFarmakologia
RodzinaProcess / pipelineProcess / pipelineProcess / pipeline
Rok powstania191319921947
TwórcaLeonor Michaelis and Maud MentenLewis Sheiner and Stephen RoushHenry Schild
Typmechanistic modeldose-response modelingantagonism quantification
Źródło pierwotneMichaelis, L., & Menten, M. L. (1913). Die Kinetik der Invertinwirkung. Biochemische Zeitschrift, 49, 333-369. link ↗Dahlström, B., & Nyberg, L. (1993). Population pharmacokinetics and pharmacodynamics. Clinical Pharmacokinetics, 24(1), 45-57. link ↗Schild, H. O. (1947). pA, a new scale for the measurement of drug antagonism. Journal of Physiology, 106(3), 337-357. DOI ↗
Inne nazwyMM kinetics, Michaelis constant, VmaxPopPD, population PD, hierarchical PD modelingSchild plot, pA2
Pokrewne233
PodsumowanieMichaelis-Menten kinetics describes the rate of enzyme-catalyzed reactions as a function of substrate concentration. Developed by Leonor Michaelis and Maud Menten in 1913, this foundational framework models enzyme catalysis through the rapid-equilibrium approximation and enables prediction of drug metabolism rates in pharmacokinetics.Population pharmacodynamic (PopPD) modeling integrates pharmacokinetics with individual dose-response relationships across patient populations to characterize drug efficacy and tolerability. Pioneered by Lewis Sheiner and colleagues, PopPD accounts for inter-individual variability in drug effects and enables rational dose optimization and response prediction.Schild analysis is a quantitative method for characterizing competitive receptor antagonism developed by Henry Schild in 1947. It uses dose-response curves in the presence and absence of antagonist to estimate the antagonist affinity constant (pA2), enabling standardized comparison of antagonist potency across drugs and experimental systems.
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ScholarGatePorównaj metody: Michaelis-Menten Kinetics · Population Pharmacodynamics · Schild Analysis. Pobrano 2026-06-19 z https://scholargate.app/pl/compare