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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.

Partial derivative—Based sensitivity analysis of models describing target-mediated drug disposition