Covariate modeling in pharmacometrics: General points for consideration

• Main Authors: Kinjal Sanghavi (Author), Jakob Ribbing (Author), James A. Rogers (Author), Mariam A. Ahmed (Author), Mats O. Karlsson (Author), Nick Holford (Author), Estelle Chasseloup (Author), Malidi Ahamadi (Author), Kenneth G. Kowalski (Author), Susan Cole (Author), Essam Kerwash (Author), Janet R. Wade (Author), Chao Liu (Author), Yaning Wang (Author), Mirjam N. Trame (Author), Hao Zhu (Author), Justin J. Wilkins (Author), for the ISoP Standards & Best Practices Committee (Author)
• Format: Book
• Published: Wiley, 2024-05-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.

Summary

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.

Item Description

2163-8306
10.1002/psp4.13115