Approaches to handling missing or “problematic” pharmacology data: Pharmacokinetics

Donald J. Irby, Mustafa E. Ibrahim, Anees M. Dauki, Mohamed A. Badawi, Sílvia M. Illamola, Mingqing Chen, Yuhuan Wang, Xiaoxi Liu, Mitch A. Phelps, Diane R. Mould

Research output: Contribution to journalArticlepeer-review

Abstract

Missing or erroneous information is a common problem in the analysis of pharmacokinetic (PK) data. This may present as missing or inaccurate dose level or dose time, drug concentrations below the analytical limit of quantification, missing sample times, or missing or incorrect covariate information. Several methods to handle problematic data have been evaluated, although no single, broad set of recommendations for commonly occurring errors has been published. In this tutorial, we review the existing literature and present the results of our simulation studies that evaluated common methods to handle known data errors to bridge the remaining gaps and expand on the existing knowledge. This tutorial is intended for any scientist analyzing a PK data set with missing or apparently erroneous data. The approaches described herein may also be useful for the analysis of nonclinical PK data.

Original languageEnglish (US)
Pages (from-to)291-308
Number of pages18
JournalCPT: Pharmacometrics and Systems Pharmacology
Volume10
Issue number4
DOIs
StatePublished - Apr 1 2021

Bibliographical note

Publisher Copyright:
© 2021 The Authors. CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics

PubMed: MeSH publication types

  • Journal Article

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