创建NONMEM数据集-如何摆脱噩梦

Shafi Chowdhury
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引用次数: 1

摘要

摘要药代动力学(pharmacokinetics, PK)是机体对药物的影响,药效学(pharmacodynamics, PD)是药物对机体的影响。在人群PK/PD分析中,使用模型预测药物对患者目标人群的影响。这种类型的分析在临床试验中变得越来越普遍,但创建广泛使用的非线性混合效果建模软件(称为NONMEM®)所需的数据集结构通常是该过程的噩梦部分。在药代动力学家觉得可以使用NONMEM数据集之前,通常需要几个月的时间来准备。它也是在解盲之后产生的,这增加了在使用它进行分析之前完成数据集的延迟。这种延迟可能导致推迟对未来试验的决定,或者在没有考虑总体PK分析报告的情况下做出这些决定。本文将着眼于在创建NONMEM数据集时导致问题的问题,以及我们可以采取的步骤……
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Creating NONMEM datasets — how to escape the nightmare
AbstractPharmacokinetics (PK) is the impact of the body on the drug and pharmacodynamics (PD) is the impact of the drug on the body. The effect of the drug on the target population of patients is predicted using models during population PK/PD analysis. This type of analysis is becoming more and more common in clinical trials, but creating the dataset structure required by the widely used non-linear mixed effects modelling software called NONMEM® is often the nightmare part of the process. It usually takes months to prepare the NONMEM dataset before the pharmacokineticist feels that it is ready for them to use. It is also produced after unblinding, adding to the delay in finalising the dataset before analysis can be performed with it. This delay can lead to holding back decisions about future trials, or those decisions are then made without taking into account the population PK analysis report. This paper will look at the issues which cause problems when creating a NONMEM dataset, and what steps we can tak...
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