Abraham Anson K, Krzyzanski Wojciech, Mager Donald E
Department of Pharmaceutical Sciences, University at Buffalo, SUNY, Amherst, NY 14260, USA.
AAPS J. 2007 Jun 8;9(2):E181-9. doi: 10.1208/aapsj0902020.
Sensitivity analysis is commonly used to characterize the effects of parameter perturbations on model output. One use for the approach is the optimization of an experimental design enabling estimation of model parameters with improved accuracy. The primary objective of this study is to conduct a sensitivity analysis of selected target-mediated pharmacokinetic models, ascertain the effect of parameter variations on model predictions, and identify influential model parameters. One linear model (Model 1, control) and 2 target-mediated models (Models 2 and 3) were evaluated over a range of dose levels. Simulations were conducted with model parameters being perturbed at the higher and lower ends from literature mean values. Profiles of free plasma drug concentrations and their partial derivatives with respect to each parameter vs time were analyzed. Perturbations resulted in altered outputs, the extent of which reflected parameter influence. The model outputs were highly sensitive to perturbations of linear disposition parameters in all 3 models. The equilibrium dissociation constant (K(D)) was less influential in Model 2 but was influential in the terminal phase in Model 3, highlighting the role of K(D) in this region. An equation for Model 3 in support of the result for K(D) was derived. Changes in the initial receptor concentration [R(tot) (0)] paralleled the observed effects of initial plasma volume (V(c)) perturbations, with increased influence at higher values. Model 3 was also sensitive to the rates of receptor degradation and internalization. These results suggest that informed sampling may be essential to accurately estimate influential parameters of target-mediated models.
敏感性分析通常用于描述参数扰动对模型输出的影响。该方法的一个用途是优化实验设计,从而能够更准确地估计模型参数。本研究的主要目的是对选定的目标介导的药代动力学模型进行敏感性分析,确定参数变化对模型预测的影响,并识别有影响力的模型参数。在一系列剂量水平下评估了一个线性模型(模型1,对照)和2个目标介导的模型(模型2和模型3)。在文献平均值的较高和较低端对模型参数进行扰动来进行模拟。分析了游离血浆药物浓度及其相对于每个参数的偏导数随时间的变化曲线。扰动导致输出改变,其程度反映了参数的影响。在所有3个模型中,模型输出对线性处置参数的扰动高度敏感。平衡解离常数(K(D))在模型2中的影响较小,但在模型3的终末相中具有影响,突出了K(D)在该区域的作用。推导了支持K(D)结果的模型3的方程。初始受体浓度[R(tot)(0)]的变化与初始血浆体积(V(c))扰动的观察效应平行,在较高值时影响增加。模型3对受体降解和内化速率也敏感。这些结果表明,明智的采样对于准确估计目标介导模型的有影响力参数可能至关重要。