REDCap and the National Mesothelioma Virtual Bank—a scalable and sustainable model for rare disease biorepositories

Abstract

Objective Rare disease research requires data sharing networks to power translational studies. We describe novel use of Research Electronic Data Capture (REDCap), a web application for managing clinical data, by the National Mesothelioma Virtual Bank, a federated biospecimen, and data sharing network. Materials and Methods National Mesothelioma Virtual Bank (NMVB) uses REDCap to integrate honest broker activities, enabling biospecimen and associated clinical data provisioning to investigators. A Web Portal Query tool was developed to source and visualize REDCap data in interactive, faceted search, enabling cohort discovery by public users. An AWS Lambda function behind an API calculates the counts visually presented, while protecting record level data. The user-friendly interface, quick responsiveness, automatic generation from REDCap, and flexibility to new data, was engineered to sustain the NMVB research community. Results NMVB implementations enabled a network of 8 research institutions with over 2000 mesothelioma cases, including clinical annotations and biospecimens, and public users’ cohort discovery and summary statistics. NMVB usage and impact is demonstrated by high website visits (>150 unique queries per month), resource use requests (>50 letter of interests), and citations (>900) to papers published using NMVB resources. Discussion NMVB’s REDCap implementation and query tool is a framework for implementing federated and integrated rare disease biobanks and registries. Advantages of this framework include being low-cost, modular, scalable, and efficient. Future advances to NVMB’s implementations will include incorporation of -omics data and development of downstream analysis tools to advance mesothelioma and rare disease research. Conclusion NVMB presents a framework for integrating biobanks and patient registries to enable translational research for rare diseases.

AutoRD: An Automatic and End-to-End System for Rare Disease Knowledge Graph Construction Based on Ontology-enhanced Large Language Models (Preprint)

“…This work exemplifies the potential of AI in medical diagnostics, even in scenarios with limited labeled data. Rashid et al [20] explored a unique approach in rare disease research through the National Mesothelioma Virtual Bank. They utilized REDCap and a web portal query tool to integrate and manage clinical data from multiple institutions.…”