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Total error-based validation including the experimental design-based robustness evaluation of a stability-indicating method for the simultaneous quantification of hydrochlorothiazide and valsartan in tablet formulations

Elkarbane M., Amood M., Bouchafra H., Azougagh M., Cherrah Y., Hubert Ph., Heyden Y., Bouklouze A.

Acta Chromatographica

2015

Vol. 27, no. 2

195--214

A gradient reversed phase high-performance liquid chromatography (RP-HPLC) method with ultraviolet (UV) detection to analyze hydrochlorothiazide (HCT) and valsartan (VS) simultaneously in a tablet formulation during forced degradation studies was developed. This method was validated using a novel approach, namely, the accuracy profile or total errors approach. The robustness of the method was evaluated using a Plackett-Burman design for eight factors. The algorithm of Dong was applied to determine the significant factor effects. The validation results showed that the method is precise (RSD: 1.14% for HCT and 0.43% for VS) and accurate (mean recovery: 99.90% for HCT and 99.98% for VS). On the other hand, the results of the robustness study showed that the type of column was the important factor which affects a number of responses, namely, the asymmetry factor (AF), retention time (RT), and resolution (RS). However, the assay results were not affected; therefore, the method can be considered robust. Finally, the method was applied to study the stability of HCT and VS under forced conditions. Significant results were obtained with basic hydrolysis, oxidation, and thermal stress, while the accelerated and acidic conditions did not affect the stability of HCT or VS.

The use of experimental design in separation science

Dejaegher B, Vander Heyden Y

Acta Chromatographica

2009

Vol. 21, no. 2

161--201

In this tutorial, the application of experimental designs in separation science is discussed. Method optimization is often divided into screening and optimization phases. In the screening step, many factors, potentially affecting the separation, are screened to identify those with the largest effects. These are then further examined in an optimization phase, to determine the best separation conditions. After optimizing the method, it should be validated, before use for quantitative purposes. Robustness testing is part of method validation and examines the effects on the responses of small changes in method conditions. During the first phase of method optimization and during robustness testing, so-called screening designs are usually applied, whereas during the second phase of optimization, response-surface designs are often used. In this tutorial, the different steps in the application of both types of design are explained and elaborated with some examples.