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Method of variability optimization in pharmacokinetic data analysis.

Grabowski T, Jaroszewski JJ, Piotrowski W, Sasinowska-Motyl M - Eur J Drug Metab Pharmacokinet (2013)

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Polpharma Biologics, Trzy lipy 3, 80-172, Gdańsk, Poland, tomasz.grabowski@polpharma.com.

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.

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Related in: MedlinePlus

Concentration–time data of itraconazole administered orally at a single dose of 100 mg for 10 male subjects before (solid line) and after transformation (dashed line). a Represents arithmetic mean and standard deviation, b shows geometric mean and standard deviation and c shows median and standard deviation
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Fig1: Concentration–time data of itraconazole administered orally at a single dose of 100 mg for 10 male subjects before (solid line) and after transformation (dashed line). a Represents arithmetic mean and standard deviation, b shows geometric mean and standard deviation and c shows median and standard deviation

Mentions: The lowest values of CV % for raw data (RD) were noted for the sampling point 48 h after the administration of the drug, and the value was 20.61 % (Table 1). It was used to transform data in the rest of the time points (1.5–35 h). The concentration values after the transformation (TD) are presented in the Table 1. Image of differences between RD and TD for the largest fluctuation of C–T curve is presented in Fig. 1. On the basis of RD and TD, CV % was calculated for MA, SDA, MG, SDG, M and SDM, which is presented in the Table 2. In relation to the value of MA, MG and M between the RD and TD data, there were no statistically significant differences (P > 0.05). No statistically significant differences (P > 0.05) were found between the mean values of individual points of concentration and the RD and TD data. The SDA value and SDG were significantly lower (P < 0.05) in relation to the RD group.Fig. 1


Method of variability optimization in pharmacokinetic data analysis.

Grabowski T, Jaroszewski JJ, Piotrowski W, Sasinowska-Motyl M - Eur J Drug Metab Pharmacokinet (2013)

Concentration–time data of itraconazole administered orally at a single dose of 100 mg for 10 male subjects before (solid line) and after transformation (dashed line). a Represents arithmetic mean and standard deviation, b shows geometric mean and standard deviation and c shows median and standard deviation
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4048666&req=5

Fig1: Concentration–time data of itraconazole administered orally at a single dose of 100 mg for 10 male subjects before (solid line) and after transformation (dashed line). a Represents arithmetic mean and standard deviation, b shows geometric mean and standard deviation and c shows median and standard deviation
Mentions: The lowest values of CV % for raw data (RD) were noted for the sampling point 48 h after the administration of the drug, and the value was 20.61 % (Table 1). It was used to transform data in the rest of the time points (1.5–35 h). The concentration values after the transformation (TD) are presented in the Table 1. Image of differences between RD and TD for the largest fluctuation of C–T curve is presented in Fig. 1. On the basis of RD and TD, CV % was calculated for MA, SDA, MG, SDG, M and SDM, which is presented in the Table 2. In relation to the value of MA, MG and M between the RD and TD data, there were no statistically significant differences (P > 0.05). No statistically significant differences (P > 0.05) were found between the mean values of individual points of concentration and the RD and TD data. The SDA value and SDG were significantly lower (P < 0.05) in relation to the RD group.Fig. 1

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Polpharma Biologics, Trzy lipy 3, 80-172, Gdańsk, Poland, tomasz.grabowski@polpharma.com.

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.

Show MeSH
Related in: MedlinePlus