发表机构
Division of Child and Adolescent Psychiatry, Cincinnati Children’s Hospital Medical Center, Ohio, USA; School of Information Technology (SoIT), University of Cincinnati, Ohio, USA（儿童与青少年精神病科，辛辛那提儿童医院医学中心，俄亥俄州，美国; 信息技术学院（SoIT），克利夫兰医学中心，俄亥俄州，美国）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对转化研究中临床生物标志物工作流程的问题，提出FMRP-LEAN架构，通过有限状态工作流程模型等技术，集成多种系统，含自动统计QC预筛选和AI操作模块，实现可追溯联系，提升工作流程可观测性等，为临床研究工作流程提供可重复模型。
AI 中文摘要
转化研究环境中的临床生物标志物工作流程通常依赖电子表格驱动的跟踪、手动质量控制（QC）核对以及松散集成的系统，导致状态可见性有限、报告延迟和操作风险增加。在基于Luminex的脆性X信使核糖核蛋白（FMRP）定量等多日检测中，这些挑战尤为突出，需要符合HIPAA标准的数据治理、确定性工作流程进展以及实验室和临床团队之间的协调沟通。本文提出了FMRP-LEAN，一种符合HIPAA标准的人工智能增强型实验室信息管理系统（LIMS）架构，通过具有明确转换保护和停留时间可观测性的有限状态工作流程模型，将生物样本生命周期管理形式化。该系统集成了部署在医院控制基础设施内的自托管Supabase/PostgreSQL堆栈、具有加密隧道和仅环回服务的混合边缘内部隔离以及双向REDCap同步。具有基于QR码跟踪的统一MRN-UUIDv7标识符框架确保在PHI驻留约束下可追溯的临床研究联系。FMRP-LEAN包含自动统计QC预筛选和一个仅对聚合预测进行操作的受治理约束的人工智能操作模块，并具有确定性回退保证。部署展示了改进的工作流程可观测性、减少的QC延迟以及实验室技术人员、研究协调员和面向患者的团队之间增强的跨角色透明度。该架构为受监管的医疗保健环境中的安全、状态明确和人工智能增强型临床研究工作流程提供了一个可重复的模型。
英文摘要
Clinical biomarker workflows in translational research settings often rely on spreadsheet-driven tracking, manual quality control (QC) reconciliation, and loosely integrated systems, resulting in limited state visibility, delayed reporting, and increased operational risk. These challenges are particularly pronounced in multi-day assays such as Luminex-based quantification of Fragile X Messenger Ribonucleoprotein (FMRP), where HIPAA-compliant data governance, deterministic workflow progression, and coordinated communication across laboratory and clinical teams are required. This paper presents FMRP-LEAN, a HIPAA-compliant, AI-augmented Laboratory Information Management System (LIMS) architecture that formalizes biospecimen lifecycle management through a finite-state workflow model with explicit transition guards and dwell-time observability. The system integrates a self-hosted Supabase/PostgreSQL stack deployed within hospital-controlled infrastructure, hybrid edge-internal isolation with encrypted tunneling and loopback-only services, and bi-directional REDCap synchronization. A unified MRN-UUIDv7 identifier framework with QR-based tracking ensures traceable clinical-research linkage under PHI residency constraints. FMRP-LEAN incorporates automated statistical QC pre-screening and a governance-constrained AI operations module that operates exclusively on aggregate projections, with deterministic fallback guarantees. Deployment demonstrates improved workflow observability, reduced QC latency, and enhanced cross-role transparency between laboratory technicians, research coordinators, and patient-facing teams. The architecture provides a reproducible model for secure, state-explicit, and AI-augmented clinical research workflows in regulated healthcare environments.
Comments15 pages, 5 figures, conference
Journal refISBCom-2026
