Department of Mathematics and Computer Science, Freie Universität, Berlin, Germany.
J Pharmacokinet Pharmacodyn. 2010 Aug;37(4):365-405. doi: 10.1007/s10928-010-9165-1. Epub 2010 Jul 27.
In drug discovery and development, classical compartment models and physiologically based pharmacokinetic (PBPK) models are successfully used to analyze and predict the pharmacokinetics of drugs. So far, however, both approaches are used exclusively or in parallel, with little to no cross-fertilization. An approach that directly links classical compartment and PBPK models is highly desirable. We derived a new mechanistic lumping approach for reducing the complexity of PBPK models and establishing a direct link to classical compartment models. The proposed method has several advantages over existing methods: Perfusion and permeability rate limited models can be lumped; the lumped model allows for predicting the original organ concentrations; and the volume of distribution at steady state is preserved by the lumping method. To inform classical compartmental model development, we introduced the concept of a minimal lumped model that allows for prediction of the venous plasma concentration with as few compartments as possible. The minimal lumped parameter values may serve as initial values for any subsequent parameter estimation process. Applying our lumping method to 25 diverse drugs, we identified characteristic features of lumped models for moderate-to-strong bases, weak bases and acids. We observed that for acids with high protein binding, the lumped model comprised only a single compartment. The proposed lumping approach established for the first time a direct derivation of simple compartment models from PBPK models and enables a mechanistic interpretation of classical compartment models.
在药物发现和开发中,经典隔室模型和基于生理学的药代动力学(PBPK)模型被成功地用于分析和预测药物的药代动力学。然而,到目前为止,这两种方法都是单独使用或并行使用的,几乎没有相互借鉴。非常需要一种直接将经典隔室模型和 PBPK 模型联系起来的方法。我们提出了一种新的机制化合并方法,用于降低 PBPK 模型的复杂性并建立与经典隔室模型的直接联系。与现有方法相比,该方法具有以下几个优点:灌注和通透性速率限制模型可以合并;合并模型允许预测原始器官浓度;并且通过合并方法保持了稳态下的分布容积。为了为经典隔室模型的开发提供信息,我们引入了最小合并模型的概念,该模型允许用尽可能少的隔室来预测静脉血浆浓度。最小合并参数值可以作为任何后续参数估计过程的初始值。我们将我们的合并方法应用于 25 种不同的药物,确定了中等至强碱、弱碱和酸的合并模型的特征。我们观察到,对于与蛋白质结合率高的酸,合并模型仅包含一个隔室。所提出的合并方法首次从 PBPK 模型直接推导出简单的隔室模型,并使经典隔室模型具有机制解释。
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