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Approaches to handling missing or “problematic” pharmacology data: Pharmacokinetics
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....
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8099444/ https://www.ncbi.nlm.nih.gov/pubmed/33715307 http://dx.doi.org/10.1002/psp4.12611 |
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author | Irby, Donald J. Ibrahim, Mustafa E. Dauki, Anees M. Badawi, Mohamed A. Illamola, Sílvia M. Chen, Mingqing Wang, Yuhuan Liu, Xiaoxi Phelps, Mitch A. Mould, Diane R. |
author_facet | Irby, Donald J. Ibrahim, Mustafa E. Dauki, Anees M. Badawi, Mohamed A. Illamola, Sílvia M. Chen, Mingqing Wang, Yuhuan Liu, Xiaoxi Phelps, Mitch A. Mould, Diane R. |
author_sort | Irby, Donald J. |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8099444 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-80994442021-05-10 Approaches to handling missing or “problematic” pharmacology data: Pharmacokinetics Irby, Donald J. Ibrahim, Mustafa E. Dauki, Anees M. Badawi, Mohamed A. Illamola, Sílvia M. Chen, Mingqing Wang, Yuhuan Liu, Xiaoxi Phelps, Mitch A. Mould, Diane R. CPT Pharmacometrics Syst Pharmacol Tutorials 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. John Wiley and Sons Inc. 2021-05-05 2021-04 /pmc/articles/PMC8099444/ /pubmed/33715307 http://dx.doi.org/10.1002/psp4.12611 Text en © 2021 The Authors. CPT:Pharmacometrics & Systems Pharmacology published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics https://creativecommons.org/licenses/by-nc/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. |
spellingShingle | Tutorials Irby, Donald J. Ibrahim, Mustafa E. Dauki, Anees M. Badawi, Mohamed A. Illamola, Sílvia M. Chen, Mingqing Wang, Yuhuan Liu, Xiaoxi Phelps, Mitch A. Mould, Diane R. Approaches to handling missing or “problematic” pharmacology data: Pharmacokinetics |
title | Approaches to handling missing or “problematic” pharmacology data: Pharmacokinetics |
title_full | Approaches to handling missing or “problematic” pharmacology data: Pharmacokinetics |
title_fullStr | Approaches to handling missing or “problematic” pharmacology data: Pharmacokinetics |
title_full_unstemmed | Approaches to handling missing or “problematic” pharmacology data: Pharmacokinetics |
title_short | Approaches to handling missing or “problematic” pharmacology data: Pharmacokinetics |
title_sort | approaches to handling missing or “problematic” pharmacology data: pharmacokinetics |
topic | Tutorials |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8099444/ https://www.ncbi.nlm.nih.gov/pubmed/33715307 http://dx.doi.org/10.1002/psp4.12611 |
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