Eco-friendly multivariant green analytical technique for the estimation of ketoconazole by UV spectroscopy in bulk and cream formulation

• Autor(a) principal: Kannaiah,Kanaka Parvathi
• Data de Publicação: 2022
• Outros Autores: Sugumaran,Abimanyu
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Química Nova (Online)
• Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-40422022000100023
• topic: ketoconazole; green analytical method; multivariant analysis; UV spectroscopy; ketoconazole cream formulation

The pharmaceutical industries are focusing on Green Analytical Chemistry principles like miniaturization, eco-friendly solvent usage, waste recycling, and analyst safety for sustainable results. A simple, eco-friendly sensitive and effective extraction and multivariant green analytical method to estimate ketoconazole in bulk and cream formulation were developed and validated according to International Council for Harmonisation (ICH) guidelines. Based on the multivariant analytical technique, the developed method built in linear regression equations between concentration and absorbance with seven different wavelengths. The validation results represent the method has linear at a concentration of 12.8-19.2 μg mL-1 with calculated Limit of Detection (LOD) and Limit of Quantification (LOQ) of 0.338 and 1.026 μg mL-1, respectively. The method results representing a precise accuracy, inter-day, and intraday precision in all the wavelengths with percentage Relative Standard Deviation (RSD) under the limits as less than 2. Also, the method was tested with two different marketed ketoconazole cream formulations with a satisfactory result. The results of the proposed method replicated the novelty in classic approaches and proved statistically. This method was confirmed as greenest than previous methods reported by using assessing tools like National Environmental Method Index (NEMI), Green Analytical Procedure Index (GAPI), Analytical eco-scale, and Analytical Greenness (AGREE) metrics. As a result, the proposed approach could widely utilize for an efficient green analytical methodology for the estimation of ketoconazole.