ArticleJournal of biomedical informatics2024
Adapting the open-source Gen3 platform and kubernetes for the NIH HEAL IMPOWR and MIRHIQL clinical trial data commons: Customization, cloud transition, and optimization.
Article in Journal of biomedical informatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Current Perspectives on the Artificial Intelligence in Critical Care Medicine.Anesthesiology clinics · 2025Review
- Automated multi-instance REDCap data synchronization for NIH clinical trial networks.JAMIA open · 2025Article
- Enhancing Gen3 for clinical trial time series analytics and data discovery: a data commons framework for NIH clinical trials.Frontiers in digital health · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
objectiveThis 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
methodsThe 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.
resultsThe 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.
conclusionThe 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.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.