Risk assessment based on spectrophotometric signals used in eco-friendly analytical scenarios for estimation of carvedilol and hydrochlorothiazide in pharmaceutical formulation.

Special attention is given to the pharmacological treatment of combined medication of Carvedilol and hydrochlorothiazide which is the most effective and the most beneficial therapy for hypertensive patients with diabetes and various metabolic comorbidities. This work represents spectrophotometric platform scenarios based on factorized spectrum (FS) using interpoint data difference resolution scenarios (IDDRS) coupled with spectrum subtraction method (SS) for the concurrent quantification of carvedilol (CAR) and hydrochlorothiazide (HCT) when present together in a combination without the need for any initial physical separation steps. This IDD resolution scenario based on manipulating the zero-order spectra (D0) of both drugs in the mixture with various spectral features at different wavelength regions (200-400 nm), region I (220-250 nm), region II (240-300 nm) and region III (270-320 nm) via absorbance resolution (AR) and induced absorbance resolution (IAR) methods coupled with corresponding spectrum subtraction (SS). The calibration curves were established across the linearity ranges of 2.0-12.0 µg/mL at 242.50 nm and 4.0-40.0 µg/mL at 285.5 nm for CAR and 1.0-11.0 µg/mL at 226.10 nm and 2.0-20.0 µg/mL at 270.5 nm for HCT. Moreover, methods' validation was confirmed via ICH guidelines. A Multicenter comparison between sensitivity, specificity in respect resolution sequence were applied using different wavelength regions with various concentration ranges was applied and finally spectral resolution recommendation is issued and cumulative validation score (CVS) is calculated as an indicator in the risk analysis. In quality control laboratories, the studied approaches are applicable for conducting analysis on the mentioned drugs. In addition, the selection of spectrophotometry aligns with the principles of green analytical chemistry, an approach that resonates with the overarching theme of minimizing environmental impact. Via four metric tools named: analytical greenness (AGREE), green analytical procedure index (GAPI), analytical eco-scale, and national environmental method index (NEMI), methods' greenness profile was guaranteed.

Spectral resolution of quaternary components in a sinus and congestion mixture; Multivariate algorithms to approach extremes of concentration levels.

Sinus and congestion mixture of three drugs and an impurity was studied for their spectral resolution using four multivariate algorithms. The studied drugs present in extremes of low and high concentrations. Low concentration levels of phenylephrine HCl and doxylamine succinate with high concentration of paracetamol along with its official impurity was a challenging mixture for pharmaceutical analysis. The developed algorithms are principal component regression, partial least squares, concentration residuals augmented classical least squares and artificial neural networks. Models were compared for their calibration errors in general and individual calibration as well as their prediction of external validation samples. Concentration levels in the designed mixture were carefully considered to recede the challenging dosage form ratio. The value of root mean square error of prediction and percentage recoveries were used to describe the analytical performance of the proposed models. Artificial neural networks provided the lower most error with good recoveries for all samples without outlier. Correlation coefficients between the predicted spectra by concentration residuals augmented classical least squares and the pure ones revealed the ability for qualitative analysis. The proposed chemometrics have been successfully used for pharmaceutical application and compared favorably with the official methods.