QbD and Six Sigma quality approach for chromatographic estimation of repurposed simvastatin from nanostructured lipid carriers

Abstract

The present research aimed to develop a simple, rapid, and sensitive RP-HPLC method for the estimation of repurposed simvastatin (SMV) from nanostructured lipid carriers (NLCs) using the quality by design (QbD) and Six Sigma approach. The method was optimized via Box-Behnken design using acetonitrile (ACN) concentration, flow rate, and injection volume as independent factors. Further, the developed method was validated pursuant to the International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH; Q2R1) guidelines. The successful chromatographic separation of SMV was achieved by an isocratic technique employing ACN: Water (70:30 v/v) mobile phase, Intersil ODS-C18 column (150 × 4.6 mm, 3.5 μm, Agilent), and flow rate of 1.0 mL/min at 238 nm. The developed method was linear over the SMV concentration range of 20–100 μg/mL. The method displayed accuracy in the range of 99.41–101.01 % and % recovery in a precision study in the range of 99.02–100.52 %. Besides, the limit of detection (LOD) and limit of quantification (LOQ) were observed to be 10.18 and 30.87 μg/mL, respectively. Shapiro-Wilk test (P = 0.5357) and Kolmogorov-Smirnov test (P > 0.10) accept the ordinariness of data. Bland-Altman plot divulged an agreeable repeatability coefficient (0.5239). Additionally, control charts like the Levey-Jennings, X-Individual, and MR charts demonstrated that the method is statistically controlled, while the CUSUM chart proved the targetability of the method. The value of process capability (Cp) was 2.23 and process capability index (Cpk) was 2.23, as shown by capability analysis, indicates the method's capacity to assess the samples precisely and consistently with the least amount of variance The developed and validated method was finally applied to ascertain the entrapment efficiency and in vitro release behaviour of SMV from NLCs. Thus, a RP-HPLC method for rapid assessment of SMV from NLCs was developed to understand influencing variables for improving the method performance. Further, the study's results manifested the worth of utilizing the response surface analysis avenue in choosing optimum critical method parameters to achieve Six Sigma quality.