We’re thrilled to announce that version 1.11.0 of CluePoints’ Central Monitoring platform, the enabling SaaS platform for Risk-Based Monitoring, will be available to users in April! Version 1.11.0 adds an abundance of new features (as requested by customers) and extensions to existing functionality.
There’s lots to cover, so let’s get started.
We have added Patient Profiles to the platform. Users can design and customize the patient profiles template using an intuitive and visual interface.
Patient profiles offer a new way to investigate atypical patients by looking at summary information from different datasets. Different data representations are available: tables, graphs, and Gantt chart.
Machine Learning(Beta Version)
Improved Key Risk Indicators
Based on the feedback we have received from our users, we have made some improvements in the Key Risk Indicators:
- No minimum volume of data required: Previously KRIs were only displayed when enough observations to fit a statistical model were available. In the new version it is possible to assess sites using KRI absolute value thresholds even if it is not yet possible to fit a statistical model.
- Improved user experience and navigation: We have added additional filters, and better organized the information on screen to facilitate the assessment and review of the KRIs.
That’s all for now!
If you would like a demonstration of the new features, please email firstname.lastname@example.org.
CluePoints is the premier provider of Risk-Based Monitoring and Data Quality Oversight Software. Our products utilize statistical algorithms to determine the quality, accuracy, and integrity of clinical trial data both during and after study conduct. Aligned with guidance from the FDA, EMA, and the new ICH (E6) addendum, CluePoints is deployed to support traditional monitoring and data management and can be implemented as the ultimate engine to drive Risk-Based Monitoring. The value of CluePoints lies in its powerful and timely ability to identify anomalous data and site errors allowing optimization of central and on-site monitoring and a significant reduction in overall regulatory submission risk.