Abstract
The literature does not provide any "high-performance thin-layer chromatographic (HPTLC)" techniques for the determination of a novel antidiabetic medicine, ertugliflozin (ERZ). Additionally, there are not many environmentally friendly analytical methods for ERZ measurement in the literature. A rapid, sensitive, and eco-friendly reversed-phase-HPTLC (RP-HPTLC) method was designed and validated in an attempt to analyze ERZ in marketed pharmaceutical tablets more precisely, accurately, and sustainably over the traditional normal-phase HPTLC (NP-HPTLC) method. The stationary phases used in the NP- and RP-HPTLC procedures were silica gel 60 NP-18F254S and 60 RP-18F254S plates, respectively. For NP-HPTLC, a chloroform/methanol (85:15 v/v) mobile phase was used. However, ethanol-water (80:20 v/v) was the preferred method for RP-HPTLC. Four distinct methodologies, including the National Environmental Method Index (NEMI), Analytical Eco-Scale (AES), ChlorTox, and Analytical GREEnness (AGREE) approaches, were used to evaluate the greenness of both procedures. For both approaches, ERZ detection was carried out at 199 nm. Using the NP- and RP-HPTLC techniques, the ERZ measurement was linear in the 50-600 and 25-1200 ng/band ranges. The RP-HPTLC method was found to be more robust, accurate, precise, linear, sensitive, and eco-friendly compared to the NP-HPTLC approach. The results of four greenness tools demonstrated that the RP strategy was greener than the NP strategy and all other reported HPLC techniques. The fact that both techniques can assess ERZ when its degradation products are present implies that they both have characteristics that point to stability-indicating features. 87.41 and 99.28%, respectively, were the assay results for ERZ in commercial tablets when utilizing the NP and RP procedures. Based on several validation and greenness metrics, it was determined that the RP-HPTLC approach was better than the NP-HPTLC method. As a result, it is possible to determine ERZ in pharmaceutical products using the RP-HPTLC approach.