Real‐world evidence in the cloud: Tutorial on developing an end‐to‐end data and analytics pipeline using Amazon Web Services resources Article Swipe
Wes Anderson
,
Roopal Bhatnagar
,
Keith Scollick
,
Marco Schito
,
Ramona Walls
,
Jagdeep T. Podichetty
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1111/cts.70078
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1111/cts.70078
In the rapidly evolving landscape of healthcare and drug development, the ability to efficiently collect, process, and analyze large volumes of real‐world data (RWD) is critical for advancing drug development. This article provides a blueprint for establishing an end‐to‐end data and analytics pipeline in a cloud‐based environment. The pipeline presented here includes four major components, including data ingestion, transformation, visualization, and analytics, each supported by a suite of Amazon Web Services (AWS) tools. The pipeline is exemplified through the CURE ID platform, a collaborative tool designed to capture and analyze real‐world, off‐label treatment administrations. By using services such as AWS Lambda, Amazon Relational Database Service (RDS), Amazon QuickSight, and Amazon SageMaker, the pipeline facilitates the ingestion of diverse data sources, the transformation of raw data into structured formats, the creation of interactive dashboards for data visualization, and the application of advanced machine learning models for data analytics. The described architecture not only supports the needs of the CURE ID platform, but also offers a scalable and adaptable framework that can be applied across various domains to enhance data‐driven decision making beyond drug repurposing.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1111/cts.70078
- OA Status
- gold
- Cited By
- 1
- References
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- Related Works
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- OpenAlex ID
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All OpenAlex metadata
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https://openalex.org/W4405376419Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1111/cts.70078Digital Object Identifier
- Title
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Real‐world evidence in the cloud: Tutorial on developing an end‐to‐end data and analytics pipeline using Amazon Web Services resourcesWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-12-01Full publication date if available
- Authors
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Wes Anderson, Roopal Bhatnagar, Keith Scollick, Marco Schito, Ramona Walls, Jagdeep T. PodichettyList of authors in order
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https://doi.org/10.1111/cts.70078Publisher landing page
- Open access
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://doi.org/10.1111/cts.70078Direct OA link when available
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Computer science, Cloud computing, Analytics, Pipeline (software), Data science, Repurposing, Raw data, Blueprint, NoSQL, World Wide Web, Database, Scalability, Engineering, Operating system, Programming language, Mechanical engineering, Waste managementTop concepts (fields/topics) attached by OpenAlex
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1Total citation count in OpenAlex
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2025: 1Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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