Generative AI for Optimal Formulary Design: Balancing Clinical Outcomes, Patient Access, and Cost Containment in Pharmacy Benefit Management

Pharmacy benefit management faces increasing complexity in designing formularies that simultaneously optimize clinical outcomes, enhance patient access, and contain costs. This research explores the innovative application of generative artificial intelligence (AI) to revolutionize formulary design and management. We developed a novel framework leveraging generative AI algorithms to analyze large-scale pharmaceutical data, predict drug utilization patterns, model outcomes, and recommend optimal formulary configurations. Our approach incorporates multi-objective optimization techniques that balance competing priorities in pharmacy benefit management. Through simulation studies and validation against historical data, we demonstrate that AI-enhanced formulary design can achieve 18.2% cost savings while maintaining or improving clinical outcomes and increasing formulary adherence by 14.6%. This research presents a significant advancement in pharmacy benefit management by providing data-driven, adaptable, and transparent formulary solutions that respond to the dynamic healthcare landscape while balancing stakeholder needs.