Green spectrophotometric method for the spectral pattern recognition based on fuzzy inference system compared to continuous wavelet transform for the quantitative determination of anti-psoriasis drugs in commercial skin ointment formulation: Comparison with HPLC

Abstract

In this study, two chemometrics methods, including fuzzy inference system (FIS) along with principal component analysis (PCA) and continuous wavelet transform (CWT) were proposed for the simultaneous spectrophotometric estimation of betamethasone dipropionate (BMD) and calcipotriol (CP) in pharmaceutical dosage form without any pretreatment. The mean recovery and root mean square error (RMSE) related to the nine rules of the FIS was 100.14%, 100.72% and 0.016 and 0.020 for BMD and CP, respectively. CWT with wavelet families of Daubechies (db2) and Coiflet (Coif2) were selected to give the best zero crossing point at a wavelength of 254 nm and 265 nm, as well as the highest coefficient of determination (R2) for BMD and CP, respectively. The limit of detection (LOD) and limit of quantitation (LOQ) were found to be 5 × 10−5, 1.7 × 10−3 μg/mL and 0.0277, 0.0225 μg/mL through the calibration graphs in the linear concentration ranges of 1–10 μg/L for BMD and CP, respectively. The selected wavelet families were successfully applied for chemometric analysis of BMD and CP in synthetic mixtures with satisfactory mean recovery values of 94.67% and 102.43% for BMD and CP, respectively. The proposed spectrophotometric methods were statistically compared to high-performance liquid chromatography (HPLC) using analysis of variance (ANOVA). The proposed analytical techniques were found to be easy, fast, precise, and robust with less solvent consumption for the concurrent analysis of BMD and CP, which can be used instead of chromatography methods in pharmaceutical quality control laboratories.