构建可追溯的药品知识管理框架，解决信息混乱与责任缺失问题。
PRISMA: Toward a Normative Information Infrastructure for Responsible Pharmaceutical Knowledge Management
- 分层设计：文档保存、语义解析、上下文展示分离处理
- 创建可问责的证据包，支持版本追踪与源头验证
- 适合药品监管、临床决策系统等需要透明性的场景
当前大多数药学AI方法将文档保存、语义理解与上下文呈现三类本质不同的操作混在同一技术层，导致溯源丢失、解释不透明、警报疲劳和责任模糊等问题。本文提出PATOS--Lector--PRISMA（PLP）架构，作为负责任药学知识管理的规范性信息基础设施。PATOS通过显式版本控制和溯源机制保存监管文档；Lector结合机器辅助阅读与人工校对，生成锚定原始文献的类型化断言；PRISMA基于RPDA框架（监管、处方、调配、给药），将同一信息核心转化为不同专业视角的上下文呈现。架构引入‘证据包’作为可问责断言的正式单元，具备版本化、可追溯、认知边界明确、经校对验证等特征，断言类型由言语行为力定义。案例研究以真实数据追踪双氢克尿噻的完整流程。该架构在巴西监管背景下开发并验证，包含超过16,000份官方文件和38个经过校对的证据包，覆盖五种参考药物。实证表明其可补足现有决策支持系统的不足，提供文档锚定、解释透明和机构问责的基础设施支撑。
原文摘要 · Abstract (English)
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.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。