Metzler C M, Tong D D
J Pharm Sci. 1981 Jul;70(7):733-7. doi: 10.1002/jps.2600700706.
The Michaelis-Menten equation has been applied successfully in the study of enzyme kinetics. It usually is used to estimate vmax and km from observations of the initial rate of reaction, v, at various substrate concentrations, Cs. A variation of this expression recently was used in pharmacokinetics, where it was assumed that the elimination rate of drug from some compartment is VC(t)/[K + C(t)], where C(t) is the drug concentration. The meaning of V and K in this context is not clear. Attempts were made to estimate V, K, and other model parameters by fitting the model to observed drug concentrations at sampling times after dosing. This paper discusses the ill-conditioning of the estimation of parameters of a differential equation that includes the so-called Michaelis-Menten output. The solution of the equation is bound by the solutions to two first-order differential equations. Parameter values in an infinite region of the parameter space are shown to have solutions also lying within these two bounds. Simulations show that a minor change in the data (observations) or in the initial estimate of the parameters may cause a large change in the final estimates. In many cases, estimation and comparison of parameter values are meaningless.
米氏方程已成功应用于酶动力学研究。它通常用于根据在不同底物浓度Cs下对反应初始速率v的观测来估算Vmax和Km。该表达式的一个变体最近被用于药代动力学,其中假设药物从某个隔室的消除速率为VC(t)/[K + C(t)],其中C(t)是药物浓度。在此背景下V和K的含义尚不清楚。人们试图通过将模型与给药后采样时间的观测药物浓度进行拟合来估算V、K和其他模型参数。本文讨论了包含所谓米氏输出的微分方程参数估计的病态问题。该方程的解受两个一阶微分方程解的约束。参数空间无限区域内的参数值被证明其解也位于这两个边界内。模拟表明,数据(观测值)或参数初始估计值的微小变化可能导致最终估计值的大幅变化。在许多情况下,参数值的估计和比较毫无意义。