开发群体药代动力学模型的全自动工具。

IF 3.1 3区 医学 Q2 PHARMACOLOGY & PHARMACY
Xiaomei Chen, Rikard Nordgren, Stella Belin, Alzahra Hamdan, Shijun Wang, Tianwu Yang, Zhe Huang, Simon J. Carter, Simon Buatois, João A. Abrantes, Andrew C. Hooker, Mats O. Karlsson
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引用次数: 0

摘要

群体药代动力学(PK)模型被广泛用于为制药公司的药物开发提供信息,并为监管机构的药物评估提供便利。开发群体 PK 模型是一个多步骤、具有挑战性且耗时的过程,其中涉及反复的人工模型拟合和评估。本文介绍了一种用于常见群体 PK 模型的全自动模型开发(AMD)工具。AMD 工具是在 Pharmpy 中实现的,Pharmpy 是一个多功能的药物计量学开源库。它由不同的模块组成,负责开发群体 PK 模型的不同组成部分,包括结构模型、个体间变异性 (IIV) 模型、事件间变异性 (IOV) 模型、残余未解释变异性 (RUV) 模型、协变量模型和异构模型。使用 10 个真实 PK 数据集对 AMD 工具进行了评估,涉及三个序列中的结构、IOV 和 RUV 模块。不同序列产生的结构模型基本一致;但 IIV 和 RUV 模型的结果存在差异。AMD 工具的最终模型显示出较低的贝叶斯信息标准(BIC)值,与现有的已发表模型相比,视觉预测检查图相似,表明除了运行时间合理外,质量也合理。模拟研究也得出了类似的结论。所开发的 AMD 工具是快速、全自动建立群体 PK 模型的理想工具,有望促进建模和模拟在药物开发中的应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A fully automatic tool for development of population pharmacokinetic models

A fully automatic tool for development of population pharmacokinetic models

Population pharmacokinetic (PK) models are widely used to inform drug development by pharmaceutical companies and facilitate drug evaluation by regulatory agencies. Developing a population PK model is a multi-step, challenging, and time-consuming process involving iterative manual model fitting and evaluation. A tool for fully automatic model development (AMD) of common population PK models is presented here. The AMD tool is implemented in Pharmpy, a versatile open-source library for pharmacometrics. It consists of different modules responsible for developing the different components of population PK models, including the structural model, the inter-individual variability (IIV) model, the inter-occasional variability (IOV) model, the residual unexplained variability (RUV) model, the covariate model, and the allometry model. The AMD tool was evaluated using 10 real PK datasets involving the structural, IIV, and RUV modules in three sequences. The different sequences yielded generally consistent structural models; however, there were variations in the results of the IIV and RUV models. The final models of the AMD tool showed lower Bayesian Information Criterion (BIC) values and similar visual predictive check plots compared with the available published models, indicating reasonable quality, in addition to reasonable run time. A similar conclusion was also drawn in a simulation study. The developed AMD tool serves as a promising tool for fast and fully automatic population PK model building with the potential to facilitate the use of modeling and simulation in drug development.

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来源期刊
CiteScore
5.00
自引率
11.40%
发文量
146
审稿时长
8 weeks
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