Supply Chain Optimization-based Drug Polymer Analysis Using AI Model for Synthesis and Characterization
Lubin Balasubramanian, G. Balamurugan, Nagamany Abirami, U Muruganantham, S. Magesh, R. Manikandan · 2025
Research on drug creation and development is crucial for chemical scientists and pharmaceutical businesses. On the other hand, drug design and discovery are hampered by limited efficacy, off-target delivery, time consumption, and excessive cost. Using the available three-dimensional structures, molecular docking can be utilised to anticipate the strength of the binding of small-molecule binders and their chemical derivatives to a macromolecular target. In process of finding as well as developing new drugs, artificial intelligence as well as machine learning technologies are essential. This chapter proposes novel technique in drug polymer-based synthesis and characterisation analysis with supply chain optimisation using artificial intelligence with machine learning algorithm. Then, the supply chain optimisation is based on drug synthesis and structure analysis using particle adversarial reinforcement Markov binary optimisation model. The experimental analysis has been carried out for various drug-polymer structure datasets in terms of prediction accuracy, random precision, and Recall.