Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, University at Buffalo, 565B Hochstetter Hall, Buffalo, NY 14260, USA.
J Pharmacokinet Pharmacodyn. 2012 Apr;39(2):141-6. doi: 10.1007/s10928-011-9233-1. Epub 2012 Jan 4.
The Michaelis-Menten (M-M) approximation of the target-mediated drug disposition (TMDD) pharmacokinetic (PK) model was derived based on the rapid binding (RB) or quasi steady-state (QSS) assumptions that implied that the target and drug binding and dissociation were in equilibrium. However, the initial dose for an IV bolus injection for the M-M model did not account for a fraction bound to the target. We postulated a correction to an initial condition that was consistent with the assumptions underlying the M-M approximation. We determined that the difference between the injected dose and one that should be used for the initial condition is equal to the amount of drug bound to the target upon reaching the equilibrium. We also observed that the corrected initial condition made the internalization rate constant an identifiable parameter that was not for the original M-M model. Finally, we performed a simulation exercise to check if the correction will impact the model performance and the bias of the M-M parameter estimates. We used literature data to simulate plasma drug concentrations described by the RB/QSS TMDD model. The simulated data were refitted by both models. All the parameters estimated from the original M-M model were substantially biased. On the other hand, the corrected M-M is able to accurately estimate these parameters except for equilibrium constant K(m). Weighted sum of square residual and Akaike information criterion suggested a better performance of the corrected M-M model compared with the original M-M model. Further studies are necessary to determine the importance of this correction for the M-M model applications to analysis of TMDD driven PK data.
基于快速结合(RB)或准稳态(QSS)假设,推导出了靶介导药物处置(TMDD)药代动力学(PK)模型的米氏-门限(M-M)近似,这些假设意味着靶和药物的结合和解离处于平衡状态。然而,M-M 模型中静脉推注的初始剂量并未考虑与靶结合的一部分。我们假设了一个与 M-M 近似假设基础一致的初始条件的修正。我们确定,注入剂量与初始条件下应使用的剂量之间的差异等于达到平衡时与靶结合的药物量。我们还观察到,修正后的初始条件使内化速率常数成为一个可识别的参数,而不是原始 M-M 模型的参数。最后,我们进行了一项模拟练习,以检查修正是否会影响模型性能和 M-M 参数估计的偏差。我们使用文献中的数据模拟了 RB/QSS TMDD 模型描述的血浆药物浓度。使用这两种模型对模拟数据进行了重新拟合。原始 M-M 模型估计的所有参数都存在显著偏差。另一方面,修正后的 M-M 模型能够准确地估计这些参数,除了平衡常数 K(m)。加权平方和残差和赤池信息量准则表明,与原始 M-M 模型相比,修正后的 M-M 模型的性能更好。需要进一步的研究来确定这种修正对于 M-M 模型在分析 TMDD 驱动的 PK 数据中的应用的重要性。