Covariate modeling in pharmacometrics: General points for consideration

IF 3.1 3区 医学 Q2 PHARMACOLOGY & PHARMACY
Kinjal Sanghavi, Jakob Ribbing, James A. Rogers, Mariam A. Ahmed, Mats O. Karlsson, Nick Holford, Estelle Chasseloup, Malidi Ahamadi, Kenneth G. Kowalski, Susan Cole, Essam Kerwash, Janet R. Wade, Chao Liu, Yaning Wang, Mirjam N. Trame, Hao Zhu, Justin J. Wilkins, for the ISoP Standards & Best Practices Committee
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引用次数: 0

Abstract

Modeling the relationships between covariates and pharmacometric model parameters is a central feature of pharmacometric analyses. The information obtained from covariate modeling may be used for dose selection, dose individualization, or the planning of clinical studies in different population subgroups. The pharmacometric literature has amassed a diverse, complex, and evolving collection of methodologies and interpretive guidance related to covariate modeling. With the number and complexity of technologies increasing, a need for an overview of the state of the art has emerged. In this article the International Society of Pharmacometrics (ISoP) Standards and Best Practices Committee presents perspectives on best practices for planning, executing, reporting, and interpreting covariate analyses to guide pharmacometrics decision making in academic, industry, and regulatory settings.

药物计量学中的共变量建模:一般考虑要点
建立协变量与药物计量模型参数之间关系的模型是药物计量分析的核心特征。通过协变量建模获得的信息可用于剂量选择、剂量个体化或规划不同人群亚组的临床研究。药物计量学文献收集了与协变量建模相关的各种复杂且不断发展的方法和解释指南。随着技术的数量和复杂性不断增加,人们开始需要一份技术现状概览。在这篇文章中,国际药物计量学会(ISoP)标准与最佳实践委员会介绍了规划、执行、报告和解释协变量分析的最佳实践,以指导学术界、工业界和监管机构的药物计量决策。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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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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