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首页> 外文期刊>Journal of pharmaceutical sciences. >Development of a hybrid physiologically based pharmacokinetic model with drug-specific scaling factors in rat to improve prediction of human pharmacokinetics
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Development of a hybrid physiologically based pharmacokinetic model with drug-specific scaling factors in rat to improve prediction of human pharmacokinetics

机译:建立具有药物特异性比例因子的大鼠混合生理学药代动力学模型,以改善对人体药代动力学的预测

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摘要

Accurate prediction of pharmacokinetics (PK) in humans has been a vital part of drug discovery. The aims of this study are to verify the usefulness of scaling factors for clearance (CL) and apparent volume of distribution at the steady state (Vss) estimated from the difference between observed and predicted PK profiles in rats for human PK prediction, and to develop a novel hybrid physiologically based pharmacokinetic (PBPK) model with the two scaling factors. The human prediction accuracies for CL with in vitro-in vivo extrapolation and Vss with a tissue composition model were improved by using rat-scaling factors. This improvement was explainable by data that the scaling factors for CL and Vss in rats were correlated with those in humans. The predictability of plasma concentration-time profiles by the hybrid PBPK model incorporating two scaling factors was compared mainly with that by the conventional PBPK model. The hybrid PBPK model yielded higher prediction accuracy for plasma concentrations than the conventional method. Furthermore, we proposed a tiered approach using the three prediction methods, including the hybrid Dedrick approach, that were previously reported (Sayama H, Komura H, Kogayu M. 2013. Drug Metab Dispos 41:498-507), taking the available information in the individual stages of drug discovery and development into consideration.
机译:人体中药代动力学(PK)的准确预测一直是药物开发的重要组成部分。这项研究的目的是验证比例因子对于清除率(CL)和稳态下的表观分布体积(Vss)的有用性,该比例因子是根据观察到的和预测的PK曲线在大鼠中的PK预测值之间的差异估算的,并开发了一个具有两个比例因子的新型杂交生理学药代动力学(PBPK)模型。通过使用大鼠比例因子,可以改善体内外推法对CL的人类预测准确性以及组织组成模型对Vss的预测准确性。这种改善可以通过数据解释,即大鼠中CL和Vss的比例因子与人类中的比例因子相关。结合了两个比例因子的混合PBPK模型的血浆浓度-时间曲线的可预测性主要与常规PBPK模型进行了比较。与传统方法相比,混合PBPK模型对血浆浓度的预测精度更高。此外,我们提出了一种使用三种预测方法的分层方法,其中包括先前报道的混合Dedrick方法(Sayama H,Komura H,Kogayu M.2013。DrugMetab Dispos 41:498-507),并采用了将药物发现和开发的各个阶段都考虑在内。

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