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Use of response surface methodology for development of new microwell-based spectrophotometric method for determination of atrovastatin calcium in tablets

期刊

CHEMISTRY CENTRAL JOURNAL
卷 6, 期 -, 页码 -

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BIOMED CENTRAL LTD
DOI: 10.1186/1752-153X-6-134

关键词

Response surface methodology; Atorvastatin; Validation; Optimization; Tablets

资金

  1. King Saud University [RGP-VPP-203]

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Background: Response surface methodology by Box-Behnken design employing the multivariate approach enables substantial improvement in the method development using fewer experiments, without wastage of large volumes of organic solvents, which leads to high analysis cost. This methodology has not been employed for development of a method for analysis of atorvastatin calcium (ATR-Ca). Results: The present research study describes the use of in optimization and validation of a new microwell-based UV-Visible spectrophotometric method of for determination of ATR-Ca in its tablets. By the use of quadratic regression analysis, equations were developed to describe the behavior of the response as simultaneous functions of the selected independent variables. Accordingly, the optimum conditions were determined which included concentration of 2,3-dichloro-5,6-dicyano-1,4-benzoquinone (DDQ), time of reaction and temperature. The absorbance of the colored-CT complex was measured at 460 nm by microwell-plate absorbance reader. The method was validated, in accordance with ICH guidelines for accuracy, precision, selectivity and linearity (r(2)= 0.9993) over the concentration range of 20-200 mu g/ml. The assay was successfully applied to the analysis of ATR-Ca in its pharmaceutical dosage forms with good accuracy and precision. Conclusion: The assay described herein has great practical value in the routine analysis of ATR-Ca in quality control laboratories, as it has high throughput property, consumes minimum volume of organic solvent thus it offers the reduction in the exposures of the analysts to the toxic effects of organic solvents, environmentally friendly Green approach) and reduction in the analysis cost by 50-fold.

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