Green spectrophotometric approaches applied to tertiary mixture for management of common cold and COVID-19 symptoms

Abstract

Recently, cold and cough dosage forms have gained significant attention due to their use in the supportive protocols for managing COVID-19 symptoms. In this study, a pharmaceutical formulation containing Paracetamol (PAR), Guaifenesin (GUA), and Phenylephrine hydrochloride (PHE) was investigated for spectral resolution and quantification using advanced spectrophotometric methods. The spectra of these components were significantly overlapped and present in their combined tablet in a challenging ratio of 250:100:5 for PAR, GUA, and PHE, respectively. The established approaches were employed for the simultaneous determination of these drugs in their pharmaceutical formulation without interference from matrix excipients. The study involved various manipulation steps, allowing each component in the combination to be analyzed by more than one approach. Integrating these methods with smart mathematical techniques, the issue of spectral data overlap was resolved without the need for preliminary separation steps. The developed methods are dual wavelength, first derivative, derivative ratio, ratio difference, constant center coupled with spectrum subtraction, and constant multiplication paired with spectrum subtraction. The proposed methods were linear over the concentration range of 3.0–35.0 μg/mL for GUA and 3.0–30.0 μg/mL for PHE. While the PAR ranges for the first derivative and constant multiplication methods were 2.5–35.0 μg/mL and 2.5–25.0 μg/mL, respectively. Excellent linearity of the suggested methods was demonstrated by the high correlation coefficients (R2), ≥ 0.9998 for all the tested compounds. These methodologies were validated according to ICH guidelines. Validation results demonstrated excellent accuracy, with recovery percentages ranging from 98 to 102 %, and precision, with RSD values less than 2 %. The obtained results were statistically compared with the official ones using F-test, Student’s t-test, and one-way ANOVA, revealing no significant differences. The proposed methods are accurate, green, smart, fast, and cost-effective. Their compliance with Green Analytical Chemistry principles was evaluated and compared to a published method using various tools to enable a more holistic evaluation from different perspectives. The promising results revealed that the investigated methods are superior green alternatives for routine analysis of the cited drugs in laboratories with limited resources and without access to expensive instruments.