Harnessing the Power of AI/ML and Risk-informed Strategies to Streamline Clinical Data Management
Ebooks
AI/ML to Support Modern Data Management
eIQ Review, part of the elluminate Clinical Data Cloud®, provides AI-enabled data review capabilities that ensure data integrity in a more efficient, scalable way.
Increase Productivity Without Sacrificing Quality
As the volume of clinical trial data from a variety of sources continues to proliferate—even the most comprehensive data review plans leave room for issues to be missed, leading to costly and time-consuming errors. With the AI-enabled data review capabilities available in eIQ Review, data review processes are transformed – increasing efficiencies and ensuring data integrity – in a scalable way.
- Anomaly detection models predict and identify subjects that have anomalous subjects or atypical values across all data sources.
- Review objectives are automated to detect anomalous data which reduces the amount of manual review required and enables reviewers to focus on the most critical data domains.
- Reviewers get a list of anomalous subjects or atypical values and can drill down to underlying subject data before taking follow-up action and creating issues directly within eIQ Review.
Optimize Time to Value
Because the detection of anomalous data is growing more difficult and time consuming as the clinical trial landscape evolves, eIQ Review was built with the end-user in mind to optimize data review processes and decrease cycle times.
- Purpose-built eIQ models are trained out-of-the-box and have minimal study start-up time.
- With self-serve, user-friendly configuration, models can be used starting day 1 of a study.
- Multiple models are available to support use-cases for clinical data review teams, medical directors and medical monitors.
FAQ
What is eIQ Review?
eIQ Review is an AI-enabled data review and query automation system designed to predict and proactively manage data issues that are both operational and context-driven.
Is eIQ Review system agnostic?
The solution is embedded within the elluminate Clinical Data Cloud and is study data agnostic.
Can algorithms run across different therapeutic areas and work on both safety and efficacy domains?
eIQ Review’s novel machine learning methodology allows the same models to be used across multiple studies and therapeutic areas and work on both safety and efficacy domains.
Why eIQ Review?
Having an AI/ML approach delivered within the elluminate Clinical Data Cloud provides users the ability to leverage existing platform capabilities – from data ingestion through insights – to issue and manage queries. These combined elements enable near real-time data review and subsequent action, all from a centralized location.
Is it possible to adjudicate a query prior to it going in the system?
The AI/ML techniques will be the drivers that identify data anomalies and outliers. Existing elluminate functionality will support the adjudication of these anomalies and the subsequent generation of issues and queries. Adjudication metrics will be fed back into the ML models to continually refine and improve the performance.
Will query analytics be provided?
Yes, there are model analytics and performance monitoring dashboards.
Is there an audit trail?
Yes, eIQ Review contains a full audit trail of findings.
