Knowledgent’s Clinical Cloud is a Platform-as-a-Service offering, powered by Amazon Web Services, that provides the infrastructure, tools, data and analytic models, pre-built data standardization processes, and adapters for organizations to rapidly develop advanced clinical informatics capabilities.
Cloud Infrastructure and Clinical Platform that Enables Use Case Driven Outcomes
Knowledgent’s Clinical Cloud is based on Amazon Web Services cloud technology with pre-built proprietary assets and accelerators customized for clinical data. These include: data cataloging, search & discovery, clinical application adapters, study data standardization, 3rd party data syndication, data & analytic models such as SDTM and ADaM, a clinical operational data mart, and visualizations. This model is built to enable clinical use case driven solutions including, but not limited to:
- Cross Study Analytics: Integrated data sets enabling better insights
- Study Operational Reporting: Better insights into your clinical trials
- Partner Collaboration: Facilitated meaningful exchanges of critical data
Knowledgent’s Clinical Cloud is powered by AWS infrastructure components, such as – EC2, VPC, Lambda, S3, and EBS, as well as database, analytics, and other platform components like EMR, Redshift, DynamoDB, Machine Learning, and QuickSight to name a few.
Why Knowledgent Clinical Cloud?
The benefits of utilizing Knowledgent’s Clinical Cloud reach across the organization:
- Can reduce spend by millions over a multi-year time span by consolidating disparate technologies and infrastructures to the cloud leveraging multiple open source software tools
- Improves time to market for realizing a variety of clinical use case by leveraging prebuilt and pre-assembled components
- Supports registration, metadata management, and analytic sandbox provisioning across all corporate data assets
- Supports exploratory analysis across hundreds of clinical trials
- Utilizes biomarker and real world evidence data to support advanced analytic use cases
- Delivers insights to refine safety signals by identifying risk factors, time to onset, and recurrence of adverse events
- Improves study design by identifying risk