A Novel Method of the Simultaneous Determination of Spironolactone and Furosemide in Pharmaceutical Tablets.

Luu, Nguyen Duy; Duyen, Tran Thi My; Luyen, Nguyen Dinh; Binh, Tran Thuc

Multivariate regression models, including classical least square, principal component regression, and partial least square, combined with UV-Vis absorbance spectra, have been developed and validated to simultaneously determine furosemide and spironolactone in tablets. The central composite design method is used to design calibration and validation concentration sets for the models. The method was applied in the concentration ranges of 4.4–15.6 mg/L for spironolactone and 2.4–13.6 mg/L for furosemide. The method exhibited good correlation coefficients (R2) with low root mean square error of calibration values of 0.22, 0.16, and 0.17 mg/L for spironolactone and 0.20, 0.17, and 0.18 mg/L for furosemide, respectively. The root mean square error of prediction values for spironolactone and furosemide are less than 10% of the average concentration values, corresponding to 1 mg/L for spironolactone and 0.8 mg/L for furosemide. Precision assessment encompassed repeatability and intermediate precision, while comparison with the HPLC method revealed no statistically significant disparity (α = 0.05). Notably, classical least square, principal component regression, and partial least square methods exhibited successful simultaneous quantification of spironolactone and furosemide within the Spiromide-40 combination tablet. Additionally, the functions and code for the analytical methods implemented in R are provided, facilitating easy usage for the readers.

FUROSEMIDE; STANDARD deviations; SPIRONOLACTONE; ROOT-mean-squares; LEAST squares; PARTIAL least squares regression

Journal of Analytical Chemistry, 2024, Vol 79, Issue 7, p923

1061-9348

Academic Journal

10.1134/S1061934824700291