首页> 美国卫生研究院文献>Frontiers in Pharmacology >Applications of linking PBPK and PD models to predict the impact of genotypic variability formulation differences differences in target binding capacity and target site drug concentrations on drug responses and variability
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Applications of linking PBPK and PD models to predict the impact of genotypic variability formulation differences differences in target binding capacity and target site drug concentrations on drug responses and variability

机译:关联的PBPK和PD模型在预测基因型变异性制剂差异目标结合能力差异和目标部位药物浓度差异对药物反应和变异性的影响中的应用

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摘要

This study aimed to demonstrate the added value of integrating prior in vitro data and knowledge-rich physiologically based pharmacokinetic (PBPK) models with pharmacodynamics (PDs) models. Four distinct applications that were developed and tested are presented here. PBPK models were developed for metoprolol using different CYP2D6 genotypes based on in vitro data. Application of the models for prediction of phenotypic differences in the pharmacokinetics (PKs) and PD compared favorably with clinical data, demonstrating that these differences can be predicted prior to the availability of such data from clinical trials. In the second case, PK and PD data for an immediate release formulation of nifedipine together with in vitro dissolution data for a controlled release (CR) formulation were used to predict the PK and PD of the CR. This approach can be useful to pharmaceutical scientists during formulation development. The operational model of agonism was used in the third application to describe the hypnotic effects of triazolam, and this was successfully extrapolated to zolpidem by changing only the drug related parameters from in vitro experiments. This PBPK modeling approach can be useful to developmental scientists who which to compare several drug candidates in the same therapeutic class. Finally, differences in QTc prolongation due to quinidine in Caucasian and Korean females were successfully predicted by the model using free heart concentrations as an input to the PD models. This PBPK linked PD model was used to demonstrate a higher sensitivity to free heart concentrations of quinidine in Caucasian females, thereby providing a mechanistic understanding of a clinical observation. In general, permutations of certain conditions which potentially change PK and hence PD may not be amenable to the conduct of clinical studies but linking PBPK with PD provides an alternative method of investigating the potential impact of PK changes on PD.
机译:这项研究旨在证明将先前的体外数据和知识丰富的基于生理的药代动力学(PBPK)模型与药效学(PDs)模型整合在一起的附加价值。这里介绍了已开发和测试的四个不同的应用程序。根据体外数据,使用不同的CYP2D6基因型开发了美托洛尔PBPK模型。将该模型用于预测药代动力学(PKs)和PD的表型差异,与临床数据相比具有优势,证明了可以在临床试验获得此类数据之前对这些差异进行预测。在第二种情况下,硝苯地平即释制剂的PK和PD数据以及控释(CR)制剂的体外溶出数据被用于预测CR的PK和PD。这种方法对制剂开发过程中的药物科学家有用。在第三个申请中使用了激动作用的操作模型来描述三唑仑的催眠作用,并且仅通过改变体外实验中与药物相关的参数就成功地将其推导至唑吡坦。这种PBPK建模方法对于比较同一治疗类别中的几种候选药物的发育科学家可能有用。最后,该模型使用游离心脏浓度作为PD模型的输入,成功地预测了白种人和韩国女性中由于奎尼丁引起的QTc延长的差异。此PBPK链接的PD模型用于证明对白人女性的游离心脏浓度奎尼丁有更高的敏感性,从而提供了对临床观察的机械理解。通常,某些条件的改变可能会改变PK,从而改变PD,可能不适用于临床研究,但是将PBPK与PD连接起来提供了另一种方法来研究PK变化对PD的潜在影响。

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