HSPiP, QbD, and Zeneth based green analysis and stability study of valsartan in the presence of mutagenic impurities: an in-silico study for predicting drug safety and quality control

Abstract

The stability of valsartan (Val) and its products (the presence of genotoxic impurities, such as N-nitrosodimethylamine as NDMA and N-nitrosodiethylamine as NDEA) is very crucial as it directly impacts safety and efficacy. Before, its product was recalled by various pharma industries due to the presence of the genotoxic impurities. It is always challenging to estimate the impurity profiling of the impurities during its shelf-life using a conventional methodology. The study addressed the HSPiP and QbD (quality by design)-driven the optimized mobile phase to improve system suitability, reliability, and sensitivity. The conventional analytical methods are less sensitive and selective in accelerated stress study for detecting the degradants and impurities. Therefore, the study addressed the combined effort of HSPiP, QbD, and in-silico tools for predicting the degradation profiling, optimizing the method, and assessing toxicity to circumvent the above limitations. Moreover, the AGREEprep and AGREE tools assessed the greenness of the method. HSPiP screened the right combination of solvents based on Hansen parameters. Zeneth evaluated the impact of the impurities on the stability. Furthermore, in-silico toxicity assessment predicted degradants to evaluate valsartan safety. The analytical method was optimized with high desirability (~ 0.98). For each stress condition, the degradants with their pathways, were predicted by employing the Zeneth software. Then, the stress study evaluated the precision of the degradants. The number of acidic, basic, oxidative, and photolysis degradants were found as 4, 3, 2, and 1, respectively, with the optimized method. The newly developed HSPiP, QbD, and Zeneth enabled stability-indicating UFLC method was environmentally sustainable, sensitive, accurate, reproducible, simple, rapid, economic, and reliable to detect even the trace degradants of VAL. x