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| Metode Chou-Talalay× | Kinetika Michaelis-Menten× | Pemodelan Farmakodinamik Populasi× | |
|---|---|---|---|
| Bidang | Farmakologi | Farmakologi | Farmakologi |
| Keluarga | Process / pipeline | Process / pipeline | Process / pipeline |
| Tahun asal≠ | 1983 | 1913 | 1992 |
| Pencetus≠ | Ting-Chao Chou and Paul Talalay | Leonor Michaelis and Maud Menten | Lewis Sheiner and Stephen Roush |
| Tipe≠ | synergy quantification | mechanistic model | dose-response modeling |
| Sumber perintis≠ | Chou, T. C., & Talalay, P. (1983). Quantitative analysis of dose-effect relationships: the combined effects of multiple drugs or enzyme inhibitors. Advances in Enzyme Regulation, 22, 27-55. DOI ↗ | Michaelis, 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 ↗ |
| Alias | CI method, Chou method, median-effect analysis | MM kinetics, Michaelis constant, Vmax | PopPD, population PD, hierarchical PD modeling |
| Terkait≠ | 3 | 2 | 3 |
| Ringkasan≠ | The Chou-Talalay method is a quantitative framework for analyzing drug interactions, developed by Ting-Chao Chou and Paul Talalay in 1983. It combines median-effect principle with the combination index (CI) to provide rigorous, model-independent assessment of synergistic, additive, or antagonistic drug effects. | Michaelis-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. |
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