Journal Article

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

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

2021

Overview

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.

• Publisher: John Wiley & Sons, Inc,John Wiley and Sons Inc,Wiley
• Subject: Accuracy / Adult / Aged / Bias / Clinical Trials as Topic / Computer Simulation - statistics & numerical data / Creatinine / Data analysis / Datasets / Drug dosages / Drug Stability / Female / Humans / Laboratories / Male / Methods / Middle Aged / Models, Biological / Models, Statistical / Parameter estimation / Patient Compliance - statistics & numerical data / Pharmacokinetics / Pharmacology - statistics & numerical data / Selection Bias / Simulation / Tutorial / Tutorials