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基于模型的长半衰期药物药代动力学药物相互作用评价经验

An experience on the model-based evaluation of pharmacokinetic drug-drug interaction for a long half-life drug.

作者信息

Hong Yunjung, Jeon Sangil, Choi Suein, Han Sungpil, Park Maria, Han Seunghoon

机构信息

PIPET (Pharmacometrics Institute for Practical Education and Training), College of Medicine, The Catholic University of Korea, Seoul 06591, Korea.

Department of Pharmacology, College of Medicine, The Catholic University of Korea, Seoul 06591, Korea.

出版信息

Korean J Physiol Pharmacol. 2021 Nov 1;25(6):545-553. doi: 10.4196/kjpp.2021.25.6.545.

Abstract

Fixed-dose combinations development requires pharmacokinetic drugdrug interaction (DDI) studies between active ingredients. For some drugs, pharmacokinetic properties such as long half-life or delayed distribution, make it difficult to conduct such clinical trials and to estimate the exact magnitude of DDI. In this study, the conventional (non-compartmental analysis and bioequivalence [BE]) and modelbased analyses were compared for their performance to evaluate DDI using amlodipine as an example. Raw data without DDI or simulated data using pharmacokinetic models were compared to the data obtained after concomitant administration. Regardless of the methodology, all the results fell within the classical BE limit. It was shown that the model-based approach may be valid as the conventional approach and reduce the possibility of DDI overestimation. Several advantages (i.e., quantitative changes in parameters and precision of confidence interval) of the model-based approach were demonstrated, and possible application methods were proposed. Therefore, it is expected that the model-based analysis is appropriately utilized according to the situation and purpose.

摘要

固定剂量复方制剂的研发需要对活性成分之间的药代动力学药物-药物相互作用(DDI)进行研究。对于某些药物,其药代动力学特性,如半衰期长或分布延迟,使得开展此类临床试验以及准确估计DDI的程度变得困难。在本研究中,以氨氯地平为例,比较了传统方法(非房室分析和生物等效性[BE])和基于模型的分析在评估DDI方面的性能。将无DDI的原始数据或使用药代动力学模型模拟的数据与联合给药后获得的数据进行比较。无论采用何种方法,所有结果均落在经典的BE限度内。结果表明,基于模型的方法可能与传统方法同样有效,并可降低DDI高估的可能性。证明了基于模型的方法的几个优点(即参数的定量变化和置信区间的精度),并提出了可能的应用方法。因此,预计基于模型的分析可根据情况和目的得到适当应用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5046/8552828/fefbc10ae801/kjpp-25-6-545-f1.jpg

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