Application of ASCA as a Multivariate Statistical Tool for Identification of Critical Parameters for Spectroscopic Determination of Dexamethasone

Document Type : Research Article


1 Pharmaceutical Analysis Research Center and Faculty of Pharmacy, Tabriz University of Medical Sciences, Tabriz, I.R. IRAN

2 Department of Chemistry, University of Mohaghegh Ardabili, Ardabil, I.R. IRAN

3 Pharmaceutical Analysis Research Center and Faculty of Pharmacy, Tabriz University of Medical Sciences, Tabriz, I.R. IRAN sciences

4 Faculty of Pharmacy, Near East University, Nicosia, North Cyprus, Mersin 10, TURKEY

5 Infectious and Tropical Diseases Research Center, Tabriz University of Medical Sciences, Tabriz, I.R. IRAN


The main goal of this study was to apply chemometrics techniques such as (ANOVA)-Simultaneous Component Analysis (ASCA), Response Surface Methodology (RSM), and Central Composite Design (CCD) to identify important factors in Dexamethasone Sodium Phosphate (DSP) microextraction from plasma samples. This work proposes the pre-concentration and determination of DSP using a Dispersive Liquid-Liquid Microextraction (DLLME) and spectrophotometry in combination with chemometrics approaches. ASCA as a multivariate statistical tool was used to more thoroughly analyze the influencing factors on DLLME and their interactions. By ASCA the diversity of the data matrix was divided into five levels for four variables: the major impact of each experimental component (dispersive and extraction solvent volume, amount of salt, and incubation time), followed by the impact of each second-order interaction. The significance of each factor or interaction effect was determined by a permutation test. The outcomes were compared with the results of the ANOVA approach to determine the ideal circumstances for measuring the trace amount of DSP. Under optimal conditions, a linear calibration curve with a detection limit of 0.071 µg/mL in the 0.1-5 µg/mL range was obtained.


Main Subjects

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