Does Price Really Matter for Generic Alternatives? Supervised learning Approaches in Deciding the Right Price for Acceptable Quality Attributes of Amlodipine Besylate among Generic Alternatives.

Abstract

The price and safety of finished pharmaceutical preparations are two major concerns while prescribing medicine. In this work, machine learning-based classification models were developed with respect to the quality attributes of 258 samples covering 9 marketed amlodipine (AMLO) formulations. The quantitation of AMLO and its three sulfonate ester genotoxic impurities of besylate counter ion was settled using a validated high-performance liquid chromatography-diode-array detection method. The classification of correlation between dependent and independent variables was exercised using linear discriminant analysis models. The linear dispersion of acceptable quality attributes was significantly different for AMLO besylate formulation with unit price per tablet "<1 Rs." Although the correlations between price and quality are well-understood associations group centroid distance for price group "2-3 Rs." and "1-2 Rs." reveal that acceptable quality dispersion was similar for both groups. Nonetheless, a higher price could allow storage of the finished formulation to be kept on the shelf for a longer period.