Evaluating the Financial Implications of AI in Drug Pricing Strategies

DOI: https://doi.org/10.63345/ijrmp.v12.i11.2

Tripti Das

Independent Researcher

West Bengal, India

Abstract

The pharmaceutical industry is undergoing a rapid transformation as artificial intelligence (AI) becomes an increasingly important tool for decision-making in drug development and pricing. This manuscript examines the financial implications of integrating AI into drug pricing strategies. By reviewing contemporary literature up to 2022 and employing a mixed-methods research approach, the study explores how AI-driven predictive analytics and machine learning models can optimize pricing decisions, reduce uncertainties in market forecasting, and influence revenue generation. Results indicate that AI applications offer substantial benefits in cost management and market responsiveness. However, challenges related to data quality, regulatory acceptance, and integration with existing healthcare systems remain. The paper concludes with recommendations for future research and strategies for pharmaceutical companies to leverage AI for sustainable competitive advantage.

Keywords

Artificial Intelligence, Drug Pricing, Financial Implications, Healthcare Economics, Machine Learning, Pharmaceutical Pricing Strategies, Cost-Benefit Analysis, Predictive Analytics

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