Abstract
The aim of this study was to develop a novel reversed-phase high-performance liquid chromatography (RP-HPLC) method for efficient separation of ivabradine and its 11 impurities. Similar polarity of impurities in the sample mixture made method optimization challenging and accomplishable only when different chemometric tools, such as principal component analysis (PCA), Box–Behnken design (BBD), and desirability function as a multicriteria approach, were employed. The presence of 3 positional isomers (impurities III, V, and VI), keto–enol tautomerism of impurity VII, and diastereoisomers of impurity X made separation of this complex mixture even more challenging. Chromatographic retention parameters obtained with the mobile phase consisting of 30 mM phosphate buffer and acetonitrile (80:20, v/v) on four different RP-HPLC columns at varying pH values (3.0, 4.0, and 5.0) were subjected to the PCA analysis to select the column with the most appropriate selectivity. Then the column temperature, pH of the aqueous component of mobile phase, phosphate buffer molarity and the organic solvent content in the mobile phase were estimated employing BBD. Valid and reliable mathematical models towards resolution of twelve critical peak pairs were obtained. After determination of the desirability making criteria for all responses, desirability functions were established and used in optimization. The proposed optimal chromatographic conditions included the Zorbax Eclipse Plus C18 chromatographic column (100 × 4.6 mm, 3.5 μm), the column temperature of 34 °C, the mobile phase flow rate of 1.6 mL min−1 and the UV detection at 220 nm. The mobile phase consisted of the 28 mM phosphate buffer at pH 6.0 and acetonitrile (85:15, v/v). Separation of one pair of positional isomers was not achieved, so methanol was added to the organic part of mobile phase in small increments with the optimal ratio of methanol to acetonitrile 59:41, v/v. The overall organic component of the mobile phase also increased to 18%, accelerating the chromatographic analysis.
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