Adapting the open-source Gen3 platform and kubernetes for the NIH HEAL IMPOWR and MIRHIQL clinical trial data commons: Customization, cloud transition, and optimization.

Autor: Adams MCB; Department of Anesthesiology, Artificial Intelligence, Translational Neuroscience and Public Health Sciences, Wake Forest University School of Medicine, Medical Center Boulevard, Winston-Salem, NC 27157, United States. Electronic address: meradams@wakehealth.edu., Griffin C; Krumware LLC, 808 Lady Street Suite D-20, Columbia, SC 29201, United States. Electronic address: colin@krum.io., Adams H; Krumware LLC, 808 Lady Street Suite D-20, Columbia, SC 29201, United States., Bryant S; Krumware LLC, 808 Lady Street Suite D-20, Columbia, SC 29201, United States., Hurley RW; Department of Anesthesiology, Translational Neuroscience, and Public Health Sciences, Wake Forest University School of Medicine, Medical Center Boulevard, Winston-Salem, NC 27157, United States., Topaloglu U; Department of Cancer Biology, Wake Forest University School of Medicine, Medical Center Boulevard, Winston-Salem, NC 27157, United States; Chief of the Clinical Translational Research Informatics Branch, National Cancer Institute, National Institutes of Health, Rockville, MD 20850, United States.
Jazyk: angličtina
Zdroj: Journal of biomedical informatics [J Biomed Inform] 2024 Nov; Vol. 159, pp. 104749. Date of Electronic Publication: 2024 Nov 06.
DOI: 10.1016/j.jbi.2024.104749
Abstrakt: Objective: This study aims to provide the decision-making framework, strategies, and software used to successfully deploy the first combined chronic pain and opioid use data clinical trial data commons using the Gen3 platform.
Materials and Methods: The approach involved adapting the open-source Gen3 platform and Kubernetes for the needs of the NIH HEAL IMPOWR and MIRHIQL networks. Key steps included customizing the Gen3 architecture, transitioning from Amazon to Google Cloud, adapting data ingestion and harmonization processes, ensuring security and compliance for the Kubernetes environment, and optimizing performance and user experience.
Results: The primary result was a fully operational IMPOWR data commons built on Gen3. Key features include a modular architecture supporting diverse clinical trial data types, automated processes for data management, fine-grained access control and auditing, and researcher-friendly interfaces for data exploration and analysis.
Discussion: The successful development of the Wake Forest IDEA-CC data commons represents a significant milestone for chronic pain and addiction research. Harmonized, FAIR data from diverse studies can be discovered in a secure, scalable repository. Challenges remain in long-term maintenance and governance, but the commons provides a foundation for accelerating scientific progress. Key lessons learned include the importance of engaging both technical and domain experts, the need for flexible yet robust infrastructure, and the value of building on established open-source platforms.
Conclusion: The WF IDEA-CC Gen3 data commons demonstrates the feasibility and value of developing a shared data infrastructure for chronic pain and opioid use research. The lessons learned can inform similar efforts in other clinical domains.
Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Research reported in this publication was supported by NIH National Institute of Biomedical Imaging and Bioengineering of the National Institutes of Health under grant number K08EB022631 and National Institute for Drug Abuse under grant numbers R24DA055306, R24DA055306-01S1, R24DA055306-02S1, and U24DA058606. This report does not represent the official view of the National Cancer Institute (NCI), the National Institutes of Health (NIH), or any part of the US Federal Government. No official support or endorsement of this article by the NCI or NIH is intended or should be inferred.
(Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)
Databáze: MEDLINE
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