Integrating AI in Pharmacy Pricing Systems to Balance Affordability, Adherence, and Ethical PBM Operations

The escalating costs of prescription medications have intensified public scrutiny of pharmacy pricing practices and the role of Pharmacy Benefit Managers (PBMs) in shaping drug affordability and accessibility.Amidst rising concerns over medication non-adherence due to cost and the opaque rebate structures of PBMs, Artificial Intelligence (AI) has emerged as a transformative solution with the potential to modernize pharmacy pricing systems.This paper explores the integration of AI technologies in pharmacy pricing frameworks to achieve a balanced triad of affordability, patient adherence, and ethical PBM operations.AIdriven platforms can process large datasets in real time to optimize pricing models, forecast demand, and detect pricing anomalies that may disadvantage patients.Machine learning algorithms enhance transparency by analyzing rebate flows, formulary decisions, and manufacturer-PBM agreements, enabling regulators and stakeholders to monitor compliance and ensure fairness.At the patient level, AI can personalize drug cost simulations and predict out-of-pocket expenses, fostering greater trust and proactive decision-making in medication management.The paper also examines ethical dimensions and policy implications of embedding AI in drug pricing systems, including risks of algorithmic bias, data privacy concerns, and the need for regulatory oversight.Case studies highlight successful implementations of AI in pharmacy benefit platforms that improved pricing transparency and medication adherence without compromising profit sustainability for stakeholders.By synthesizing current technological, regulatory, and ethical trends, this paper proposes a multi-layered model for responsible AI integration in pharmacy pricing.It advocates for collaborative frameworks that align the interests of patients, pharmacies, PBMs, and policymakers-ultimately advancing a data-driven, equitable pharmaceutical pricing ecosystem.