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 professional views. The architecture introduces the Evidence Pack as a formal unit of accountable assertion (versioned, traceable, epistemically bounded, and curatorially validated), with assertions typified by illocutionary force. A worked example traces dipyrone monohydrate across all three layers using real system data. Developed and validated in Brazil's regulatory context, the architecture is grounded in an operational implementation comprising over 16,000 official documents and 38 curated Evidence Packs spanning five reference medications. The proposal is demonstrated as complementary to operational decision support systems, providing infrastructural conditions that current systems lack: documentary anchoring, interpretive transparency, and institutional accountability.

翻译：当前大多数药学领域的人工智能方法将三种认识论上截然不同的操作——文档保存、语义解释和情境呈现——合并到单一技术层中。这种混淆是导致反复出现脆弱性的根本原因，包括溯源丢失、解释不透明、警报疲劳和责任弱化。本文提出PATOS-Lector-PRISMA（PLP）基础设施，作为负责任药品知识管理的规范性信息架构。PATOS通过显式版本控制和溯源机制保存监管文档；Lector实现机器辅助阅读与人工策展相结合，生成锚定于原始来源的定型断言；PRISMA通过RPDA框架（监管、处方、配发、管理）提供情境化呈现，将同一信息核心折射为不同的专业视图。该架构引入"证据包"作为责任断言的形式化单元（版本化、可追溯、认识论有界且经策展验证），断言依据言外之力进行类型化。通过一个实际案例，利用真实系统数据追踪一水安乃近在三个层级间的流转。该架构在巴西监管背景下开发并验证，基于一个包含超过16,000份官方文档和涵盖五种参考药物的38个经策展证据包的实际部署实现。本提案被证明可与运营决策支持系统互补，提供当前系统所缺乏的基础设施条件：文档锚定、解释透明度和制度问责性。