Machine Learning-Assisted Simultaneous Estimation of Aspirin and Dipyridamole Using UV–Visible Spectrophotometer

Simultaneous estimation of Aspirin (ASP) and Dipyridamole (DIP) was developed using UV– visible spectrophotometer. Multicomponent analysis mode was used for the estimation of both drugs at their respective wavelength maxima. Both drugs were found to be linear within the concentration range of 5-30 µg/mL. The correlation coefficient (R2 value) of ASP and DIP were found to be 0.995 and 0.996 respectively. Method validation parameters such as accuracy, precision, and recovery studies were found to be within acceptable ICH limits. H point standard addition method (HPSAM) was developed for the estimation of both the drugs at the selected isosbestic points namely 218 and 226nm. Python code was developed to calculate the validation parameters of the developed methods. The percentage purity for both methods was found to be within the range of 94.4 to 106.84%. The relative standard deviation (RSD) of ASP and DIP was found to be 2.26 and 2.21 respectively and the percentage recovery was in the range from 93.41 to 94.59%. Green metrics was performed using AGREE software and the developed methods show greenness with a score of 0.79. Both the methods were found to be accurate and precise. The developed Python code offers additional support in plotting the graph and in the calculation of different parameters. An attempt was made to develop an APP using the optimized Python code for calculating HPSAM and Multi-component method validation parameters. Keywords: Simultaneous estimation, HPSAM, isosbestic points, UV Vis spectroscopy, Python, Multicomponent Analysis