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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....

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Autores principales: 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.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
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.
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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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