Gibiansky Leonid, Gibiansky Ekaterina, Kakkar Tarundeep, Ma Peiming
QuantPharm LLC, North Potomac, MD, USA.
J Pharmacokinet Pharmacodyn. 2008 Oct;35(5):573-91. doi: 10.1007/s10928-008-9102-8. Epub 2008 Nov 13.
Models for drugs exhibiting target-mediated drug disposition (TMDD) play an important role in the investigation of biological products (Mager and Jusko 2001). These models are often overparameterized and difficult to converge. A simpler quasi-equilibrium (QE) approximation of the general model has been suggested (Mager and Krzyzanski 2005), but even this simpler form can be overparameterized when, for example, drug target level is not available. This work (a) introduces quasi-steady-state (QSS) and Michaelis-Menten (MM) approximations of the TMDD model, (b) derives the relationships between the parameters of the TMDD, QE, QSS and MM models, (c) investigates the parameter ranges where the simplified approximations are equivalent to the TMDD model, (d) proposes an algorithm for establishing identifiability of these models, and (e) tests this algorithm on simulated datasets. The proposed QSS approximation is more general than the QE approximation: it degenerates into the QE approximation when the internalization rate of the drug-target complex is much smaller than its dissociation rate. The proposed identifiability analysis algorithm may be applied to provide justification for use of simplified approximations, avoiding use of incorrect parameter estimates of over-parameterized TMDD models while simultaneously saving time and resources required for the pharmacokinetics analysis of drugs with TMDD. The utility of the derived approximations and of the identifiability algorithm was demonstrated on the examples of the simulated data sets. The simulation examples indicated that the QSS model may be preferable to the QE model when the internalization rate of the drug-target complex significantly exceeds its dissociation rate. The MM approximation may be adequate when the drug concentration significantly exceeds the target concentrations or when the target occupancy is close to 100%.
表现出靶点介导药物处置（TMDD）的药物模型在生物制品研究中发挥着重要作用（Mager和Jusko，2001年）。这些模型往往参数过多且难以收敛。有人提出了一种更简单的通用模型准平衡（QE）近似法（Mager和Krzyzanski，2005年），但即使是这种更简单的形式，在例如药物靶点水平不可用时也可能参数过多。这项工作：（a）引入了TMDD模型的准稳态（QSS）和米氏（MM）近似法；（b）推导了TMDD、QE、QSS和MM模型参数之间的关系；（c）研究了简化近似法与TMDD模型等效的参数范围；（d）提出了一种确定这些模型可识别性的算法；（e）在模拟数据集上测试了该算法。所提出的QSS近似法比QE近似法更具通用性：当药物 - 靶点复合物的内化速率远小于其解离速率时，它会退化为QE近似法。所提出的可识别性分析算法可用于为简化近似法的使用提供依据，避免使用参数过多的TMDD模型的错误参数估计，同时节省具有TMDD的药物药代动力学分析所需的时间和资源。在模拟数据集的示例中证明了所推导近似法和可识别性算法的实用性。模拟示例表明，当药物 - 靶点复合物的内化速率显著超过其解离速率时，QSS模型可能比QE模型更可取。当药物浓度显著超过靶点浓度或靶点占有率接近100%时，MM近似法可能是合适的。
