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ATRI LIMS: a cloud-native open-source laboratory information management system for biomarker-driven Alzheimer's
Gustavo A Jimenez-Maggiora1, Stefania Bruschi1, Sara Abdel-Latif1
1Epstein Family Alzheimer's Therapeutic Research Institute, Keck School of Medicine of the University of Southern California, San Diego, CA 92121, United States.
Objectives:
This article summarizes the architecture, design principles, and implementation strategy of the ATRI Laboratory Information Management System (LIMS), a cloud‑native, open‑source platform supporting biomarker‑driven Alzheimer's disease (AD) clinical research. The system addresses challenges associated with managing large‑scale, multimodal biomarker, and biobanking data across multisite studies.
Methods:
The ATRI LIMS employs a Model-View-Controller architecture implemented in Django, with Single‑Page Application interfaces built in ReactJS. A hybrid database model integrates a normalized core schema with study‑specific extensions. Deployment on Amazon Web Services incorporates multifactor authentication, encryption, and a web application firewall. Regulatory support is provided through audit trails and electronic signatures. Development relied on collaboration between informatics engineers and laboratory personnel, with user acceptance testing guiding workflow and interface refinement.
Results:
As of February 2026, the ATRI LIMS supports seven clinical trials and observational studies and manages more than 1.2 million biospecimens. The platform synchronizes biospecimen metadata and assay outputs with clinical datasets, improves operational efficiency through automated workflows and quality control, and facilitates compliant sample sharing for secondary research. AI‑assisted development accelerated feature delivery while maintaining code quality.
Discussion:
The ATRI LIMS offers a scalable, adaptable informatics framework for biomarker‑intensive AD research. Its modular design, cloud‑native architecture, and comprehensive data management capabilities support accurate specimen tracking and coordinated data integration. An open-source release is planned to enable adoption and adaptation by other research programs.
Conclusions:
The ATRI LIMS enhances informatics infrastructure for modern AD research by enabling scalable, efficient, and compliant biomarker and biospecimen workflow management.