en
Scientific article
Review
English

Parametric and Nonparametric Methods in Population Pharmacokinetics: Experts' Discussion on Use, Strengths, and Limitations

Published inJournal of clinical pharmacology, vol. 62, no. 2, p. 158-170
Publication date2022-02
First online date2021-12-03
Abstract

Population pharmacokinetics consists of analyzing pharmacokinetic (PK) data collected in groups of individuals. Population PK is widely used to guide drug development and to inform dose adjustment via therapeutic drug monitoring and model-informed precision dosing. There are 2 main types of population PK methods: parametric (P) and nonparametric (NP). The characteristics of P and NP population methods have been previously reviewed. The aim of this article is to answer some frequently asked questions that are often raised by scholars, clinicians, and researchers about P and NP population PK methods. The strengths and limitations of both approaches are explained, and the characteristics of the main software programs are presented. We also review the results of studies that compared the results of both approaches in the analysis of real data. This opinion article may be informative for potential users of population methods in PK and guide them in the selection and use of those tools. It also provides insights on future research in this area.

eng
Keywords
  • MIDD (model-informed drug development)
  • Modeling and simulation
  • Pharmacometrics
  • Population pharmacokinetics
  • Therapeutic drug monitoring
  • Age Factors
  • Algorithms
  • Area Under Curve
  • Humans
  • Metabolic Clearance Rate
  • Models, Biological
  • Models, Statistical
  • Pharmacokinetics
  • Sex Factors
  • Software Design
Citation (ISO format)
GOUTELLE, Sylvain et al. Parametric and Nonparametric Methods in Population Pharmacokinetics: Experts” Discussion on Use, Strengths, and Limitations. In: Journal of clinical pharmacology, 2022, vol. 62, n° 2, p. 158–170. doi: 10.1002/jcph.1993
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Article (Published version)
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Identifiers
ISSN of the journal0091-2700
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