Post COVID-19 Supply Chain Optimization for the Indian Pharmaceutical Industry using AI Techniques

Abstract

The COVID-19 pandemic has overwhelmed healthcare systems around the globe, having an indirect effect on the treatment of other diseases. During these unprecedented times the Indian pharmaceutical industry has been busy responding to all the sudden healthcare challenges that were arising from the disruption in supply chains, and this has showcased a necessity to improve functioning of the industry. Overall, India is one the fastest emerging pharmaceutical markets but many faults from the past decade in the Indian supply chain system have been highlighted by this pandemic. This paper discusses the critical elements of any supply chain and the various strategies that a pharmaceutical company can use to function efficiently. Some of the more modern approaches used by companies are artificial intelligence (AI) and machine learning (ML) tools in supply chain optimization. These new technologies help reduce lead times, significantly lower costs and help predict better routes for the future. The paper then analyzes an active pharmaceutical ingredient (API), paracetamol which is a highly produced drug in India. Evaluating its current production in the supply chain process, the paper suggests ways to improve supply chain for this particular API in India. All in all, improving the supply chain management in India by developing coherent strategies and making data-driven decisions has the potential to improve organizational profitability.