Problem
Research questions and friction points this paper is trying to address.
clinical biomarker workflow
HIPAA compliance
laboratory information management
workflow observability
data governance
FMRP-LEAN: A HIPAA-Compliant AI-Augmented LIMS Architecture for End-to-End Clinical Assay Workflow Optimization
🤖 AI Summary
This work addresses the opacity, reporting delays, and compliance risks inherent in clinical biomarker workflows—particularly pronounced in multi-day FMRP assays—stemming from reliance on spreadsheets and manual quality control. The authors propose a HIPAA-compliant, AI-augmented Laboratory Information Management System (LIMS) that models the entire sample lifecycle using a finite state machine, ensuring explicit state representation, controlled transitions, and observable dwell times. A novel MRN-UUIDv7 unified identifier combined with QR-code tracking enables end-to-end traceability under PHI residency constraints. Governance-constrained AI operates exclusively on aggregated projections, complemented by a deterministic fallback mechanism. Built on a hospital-hosted Supabase/PostgreSQL stack with hybrid isolation architecture, the system supports bidirectional REDCap synchronization and secure linkage between clinical and research data. Deployment markedly enhances workflow observability, reduces QC latency, and improves cross-role collaboration transparency.
📝 Abstract
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.
Innovation
Methods, ideas, or system contributions that make the work stand out.
AI-augmented LIMS
finite-state workflow
HIPAA-compliant architecture
PHI-resident identifier
aggregate-projection AI
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