BRIEF RESEARCH REPORT article
Front. Digit. Health
Sec. Health Technology Implementation
Volume 7 - 2025 | doi: 10.3389/fdgth.2025.1570009
This article is part of the Research TopicUnlocking the Potential of Health Data: Interoperability, Security, and Emerging Challenges in AI, LLM, Precision Medicine, and Their Impact on Healthcare and ResearchView all 5 articles
Enhancing Gen3 for Clinical Trial Time Series Analytics and Data Discovery: A Data Commons Framework for NIH Clinical Trials
Provisionally accepted
- 1School of Medicine, Wake Forest University, Winston-Salem, United States
- 2Krumware LLC, Columbia, SC, United States
- 3National Institutes of Health (NIH), Bethesda, Maryland, United States
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This work presents a framework for enhancing Gen3, an open-source data commons platform, with temporal visualization capabilities for clinical trial research. We describe the technical implementation of cloud-native architecture and integrated visualization tools that enable standardized analytics for longitudinal clinical trial data while adhering to FAIR principles. The enhancement includes Kubernetes-based container orchestration, Kibana-based temporal analytics, and automated ETL pipelines for data harmonization. Technical validation demonstrates reliable handling of varied time-based data structures, while maintaining temporal precision and measurement context. The framework's implementation in NIH HEAL Initiative networks studying chronic pain and substance use disorders showcases its utility for real-time monitoring of longitudinal outcomes across multiple trials. This adaptation provides a model for research networks seeking to enhance their data commons capabilities while ensuring findable, accessible, interoperable, and reusable clinical trial data.
Keywords: data commons, Cloud computing, opioid, Chronic Pain, Kubernetes, Gen3, timeseries, Patient Reported Outcomes
Received: 02 Feb 2025; Accepted: 23 Jun 2025.
Copyright: © 2025 Adams, Griffith, Adams, Bryant, Hurley and Topaloglu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Meredith C. B. Adams, School of Medicine, Wake Forest University, Winston-Salem, United States
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