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- Title
Impact of Logarithmic Transformation on the Restoration of Normality in the Bioequivalence Data of Glimepiride 4 mg tablet.
- Authors
Ishrat, Ghazala; Al-Shami, Munther; Nawaz, Muhammad; Rizwani, Ghazala H.
- Abstract
The Bioequivalence (BE) study data is mostly assumed to be normally distributed but Skewness is also a common feature of it and the Logarithmic Transformation (LT) of such data is widely applied to address this issue. After which the normality is supposedly assumed but this may not be true unless the fundamental assumption of the normal distribution of randomly generated data is verified. In some cases, instead of normality restoration, LT may introduce new problems like inducing skewness and increased variability, which is more difficult to handle. The data of a 2 x 2 BE study of Glimepiride 4 mg Test (T) and Reference (R) tablets, were used. After the drugs administration, blood samples were collected on pre-determined intervals and the plasma drug levels were determined by a validated analytical procedure. The Pharmacokinetic (PK) parameters, AUC0t, AUC08) and Cmax were derived. The data, was statistically analyzed on the linear and LT scale and a comparison between the two approaches was established, using 90% Confidence Interval (CI), two one-sided testing of hypothesis (TOST), ANOVA, Shapiro-Wilk and Q-Q Plots, using Biostat® software. The results of T and R for Pharmacokinetic metrics, 90% CI and ANOVA on linear and log scale, ANOVA, assessment of Normality restoration by Shapiro-Wilk test and Q-Q plots of the Studentized intra and inter- subject residuals are given in the relevant tables. No significant difference in the results of both approaches was found. The preliminary evidence of the weaknesses and shortcoming of the statistical procedures in normality assumption is identified. It may be concluded that LT is likely to produce inconsistent outcome regarding the restoration of normality. Since there was no significant difference in both approaches, it may be more appropriate to switch to the other distribution-free methods like Wilcoxon-Mann-Whitney two one-sided test (TOST) or the other newer analytic distribution-free methods, like the generalized estimating equations (GEE). An additional exploration is required to strengthen this notion and to identify the circumstances where the deterministic parameters are ascertained to select a suitable model for the data analysis and conclusion.
- Subjects
GENERALIZED estimating equations; FOREST measurement; GAUSSIAN distribution; FOREST restoration; PHARMACOKINETICS
- Publication
Current Trends in Biotechnology & Pharmacy, 2020, p51
- ISSN
0973-8916
- Publication type
Article