FMRP-LEAN: A HIPAA-Compliant AI-Augmented LIMS Architecture for Clinical Biomarker Workflows

Forum topic · 小凯 · 2026-07-24

Summary

Researchers Eva McCord, Ernest Pedapati, and Zag ElSayed present FMRP-LEAN (arXiv:2507.18396), a HIPAA-compliant, AI-augmented Laboratory Information Management System (LIMS) architecture designed for translational research biomarker workflows. The paper targets common problems in spreadsheet-driven tracking: limited state visibility, delayed reporting, and manual quality control (QC) reconciliation, which are especially acute in multi-day assays such as Luminex-based quantification of Fragile X Messenger Ribonucleoprotein (FMRP). The architecture formalizes biospecimen lifecycle management with a finite-state workflow model featuring explicit transition guards and dwell-time observability. It integrates a self-hosted Supabase/PostgreSQL stack deployed within hospital-controlled infrastructure, hybrid edge-internal isolation with encrypted tunnels and loopback-only services, and bidirectional REDCap synchronization. A unified MRN-UUIDv7 identifier scheme with QR-based tracking preserves traceable clinical research linkage under PHI residency constraints. The system includes automated statistical QC pre-screening and a governance-constrained AI operations module that runs only on aggregated projections with deterministic fallback guarantees. Deployment showed improved workflow observability, reduced QC latency, and better cross-role transparency among lab technicians, research coordinators, and patient-facing teams.

Overview

Field: Machine Learning Authors: Eva McCord, Ernest Pedapati, Zag ElSayed Published: 2026-07-24 arXiv: 2507.18396

Abstract (translated from the forum post)

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.

Key Architectural Components

Self-hosted Supabase/PostgreSQL stack deployed inside hospital-controlled infrastructure
Hybrid edge-internal isolation with encrypted tunnels and loopback-only services
Bidirectional REDCap synchronization for clinical data integration
Unified MRN-UUIDv7 identifier framework with QR-based tracking, ensuring traceable clinical research linkage under PHI residency constraints
Automated statistical QC pre-screening
Governance-constrained AI operations module that operates only on aggregated projections with deterministic fallback guarantees

Results

Deployment demonstrated improved workflow observability, reduced QC latency, and enhanced cross-role transparency among laboratory technicians, research coordinators, and patient-facing teams. The architecture offers a replicable model for secure, state-explicit, and AI-augmented clinical research workflows in regulated healthcare environments.

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*Auto-collected on 2026-07-24. Full abstract: arxiv.org/abs/2507.18396*