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稳态预测对参数估计误差的敏感性的解析近似:II. 米氏动力学

Analytical approximations of sensitivities of steady state predictions to errors in parameter estimation: II. Michaelis-Menten kinetics.

作者信息

Gonda I

出版信息

J Pharmacokinet Biopharm. 1984 Oct;12(5):525-34. doi: 10.1007/BF01060130.

Abstract

Linear sensitivity theory is used to estimate the reliability of predictions of the minimum and maximum concentrations at steady state in the Michaelis-Menten model with i.v. bolus. The dependence of the relative errors in the predictions on the errors in the pharmacokinetic parameters is derived in an analytical form. It is shown that the quality of the predictions is not equally sensitive to all errors in parameters, and that the sensitivity factors vary with the degree of saturation of the system. An example of application for a drug, such as phenytoin, is discussed. It is suggested that sensitivity analysis may be useful in design of pharmacokinetic experiments aimed at the control of steady state levels for drugs with Michaelis-Menten kinetics.

摘要

线性灵敏度理论用于估计静脉推注给药的米氏模型中稳态时最小和最大浓度预测的可靠性。以解析形式推导了预测中的相对误差对药代动力学参数误差的依赖性。结果表明,预测质量对参数中的所有误差并非同等敏感,且灵敏度因子随系统的饱和程度而变化。文中讨论了一种药物(如苯妥英)的应用实例。建议灵敏度分析在旨在控制具有米氏动力学的药物稳态水平的药代动力学实验设计中可能有用。

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