PRISMA: Toward a Normative Information Infrastructure for Responsible Pharmaceutical Knowledge Management
Eugenio Rodrigo Zimmer Neves, Amanda Vanon Correa, Camila Campioni, Gabielli Pare Guglielmi, Bruno Morelli

TL;DR
The paper introduces PRISMA, a normative information architecture for responsible pharmaceutical knowledge management, addressing issues of provenance, interpretability, and accountability in AI systems for pharmacy.
Contribution
It proposes the PATOS-Lector-PRISMA infrastructure, including formal units of accountable assertions and a multi-layered presentation framework, validated with real regulatory data in Brazil.
Findings
Implemented with over 16,000 documents and 38 Evidence Packs.
Demonstrated improved provenance, transparency, and accountability.
Complementary to existing decision support systems.
Abstract
Most existing approaches to AI in pharmacy collapse three epistemologically distinct operations into a single technical layer: document preservation, semantic interpretation, and contextual presentation. This conflation is a root cause of recurring fragilities including loss of provenance, interpretive opacity, alert fatigue, and erosion of accountability. This paper proposes the PATOS--Lector--PRISMA (PLP) infrastructure as a normative information architecture for responsible pharmaceutical knowledge management. PATOS preserves regulatory documents with explicit versioning and provenance; Lector implements machine-assisted reading with human curation, producing typed assertions anchored to primary sources; PRISMA delivers contextual presentation through the RPDA framework (Regulatory, Prescription, Dispensing, Administration), refracting the same informational core into distinct…
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