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Resolution of five-component mixture using mean centering ratio and inverse least squares chemometrics
Mahmoud Mohamed Issa1, R'afat Mahmoud Nejem, Alaa Mohamed Abu Shanab
1Analytical Chemistry, Department of Chemistry, Alaqsa University, P,O,Box 4051, Gaza, Palestine. rafat_nejem@yahoo.com.
This study compares two chemometric methods, mean centering of ratio spectra and inverse least squares, for simultaneously determining five pharmaceutical compounds. Both methods demonstrated high accuracy and efficiency in analyzing complex mixtures like Decamol Flu syrup.
Area of Science:
- Analytical Chemistry
- Chemometrics
- Pharmaceutical Analysis
Background:
- Simultaneous determination of multiple pharmaceutical compounds presents analytical challenges.
- Existing methods may lack the resolution required for complex mixtures.
- Chemometric techniques offer advanced solutions for resolving overlapping spectra.
Purpose of the Study:
- To compare the efficacy of mean centering of ratio spectra and inverse least squares for simultaneous analysis.
- To validate these methods for quantifying five specific pharmaceutical compounds.
- To assess their applicability in analyzing a real-world pharmaceutical product.
Main Methods:
- Method I: Mean centering of ratio spectra involving four steps to enhance signal-to-noise ratio.
- Method II: Inverse least squares utilizing an updated multivariate calibration model.
- Spectrophotometric analysis of prepared mixtures within specific UV-Vis ranges (220-280 nm and 230-270 nm).
Main Results:
- Both methods achieved high mean recoveries (99.9-101.3%) across various linear concentration ranges.
- Successful prediction of a five-component mixture in Decamol Flu syrup was demonstrated.
- The methods exhibited good selectivity, high sensitivity, and extremely low detection limits.
Conclusions:
- No prior methods exist for the simultaneous determination of this specific five-component mixture.
- The mean centering of ratio spectra and inverse least squares methods are comparable in performance.
- Statistical analysis (t-test and F-ratio) showed no significant difference between the two methods.
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