Method of variability optimization in pharmacokinetic data analysis

Abstract

For many drugs administered per os, high variability in the concentration–time (C–T) values from first sampling to the phase of distribution may cause difficulty in pharmacokinetic analysis. Therefore, the aim of this study was to propose a method of transformation of C–T data, which would allow significantly reducing the standard deviation (SD) value of observed concentrations, without a statistically significant influence on the value of the mean for each sampling point in group. In the presented study, the lowest value of relative standard deviation of concentrations observed in the elimination phase and the value of precision of the used analytical method, were used to optimize the arithmetic, geometric means, median, and the value of SD obtained after single oral administration of itraconazole in human subjects. Non-compartmental modeling was used to estimate pharmacokinetic parameters. The analysis of SD pharmacokinetic parameters after C–T value optimization indicated more than twice the lower value of SD. After transforming the itraconazole data, lower variability of concentration data gives more selective pharmacokinetics profile in absorption and early distribution phase.

The First Physiologically Based Pharmacokinetic (PBPK) Model for an Oral Vaccine Using Alpha-Tocopherol as an Adjuvant

“…The AUC represents the integral of drug concentration with respect to time, and it provides valuable information about drug absorption, distribution, metabolism, and elimination. Comparing AUC values is crucial in pharmacology as it helps assess the overall exposure and effectiveness of different drugs or formulations, as comparing drug formulations or dosage regimens, comparing different drugs, assessing drug–drug interactions, predicting therapeutic effects, bioequivalence studies, and pharmacokinetic studies [ 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 ].…”