AI-Powered Regulatory Surveillance for Mitigating Pharmaceutical Manufacturer Product Hopping under the IRA

Abstract

The Inflation Reduction Act (IRA) of 2022 aims to curb soaring pharmaceutical costs by mandating price negotiation for Qualifying Single Source Drugs (QSSDs) that have been on the market for 7 (small molecules) or 11 (biologics) years and lack generic competition. However, this time-based metric introduces a critical systemic vulnerability: Product Hopping (PH). PH is an established anticompetitive tactic wherein manufacturers introduce minor, non-therapeutic reformulations (a New Drug Application (NDA) or Biologics License Application (BLA)) solely to reset the negotiation clock, thereby extending their monopoly. Current reactive regulatory frameworks are insufficient to counteract these complex, data-driven manipulative strategies. This theoretical paper proposes an expert-level conceptual framework for an Artificial Intelligence (AI)-powered Regulatory Surveillance Architecture (RSA) within the Centers for Medicare & Medicaid Services (CMS). This RSA leverages predictive analytics, Natural Language Processing (NLP), and anomaly detection across multi-modal data streams—including patent filings, clinical trial documents, and market data—to quantify the economic and therapeutic rationale underlying reformulation, yielding a Probabilistic Intent Score (PIS). Central to the framework is the mandatory implementation of Explainable AI (XAI) to ensure that regulatory interventions, particularly those triggering high-stakes negotiation, are transparent, auditable, and legally defensible, meeting rigorous standards of administrative due process and governance.