CluePoints, a provider of statistical and AI-driven software solutions, and the FDA have extended their long-standing collaboration.
 
Under the original CRADA between FDA and CluePoints, software was developed and CluePoints’ existing software was enhanced to produce a ranked list of anomalous sites to help prioritize site inspection(s) for FDA inspectors.
 
As a result of the original CRADA, the CluePoints software was deployed in the FDA high performance computing environment, new statistical tests were developed to detect anomalous sites, the site ranking algorithm was improved, and the user interface for use by reviewers and others at FDA was also improved. Additionally, significant progress was made in the detection of modulators of treatment effect, i.e., factors such as center, region, or country that have a statistically significant impact on the magnitude of treatment effect.
 
Under this new proposed CRADA, FDA and CluePoints, Inc. will focus on two primary objectives:
 

• To develop and enhance CluePoints SMART software to address a broader range of regulatory issues and concerns. The CRADA will leverage date/time data which takes on greater significance with decentralized trials (DCT) and the increasing use of electronic clinical outcome assessment (eCOA) and electronic patient reported outcomes (ePRO) technologies. Further developments will be added to improve the detection of duplicate patients. The proposed CRADA will explore how Artificial Intelligence and Machine Learning (AI/ML) algorithms can further support anomaly detection. Finally, further research will be carried out to explore the moderators of treatment effect and develop a software solution that can be deployed within the FDA environment.
• To improve and enhance how SMART software and the CluePoints monitoring platform may be adapted to better support FDA processes related to anomaly detection, review and follow-up, as well as site selection for FDA inspections.

 
Anticipated benefits of the CRADA to the FDA include improved detection of anomalous sites, the ability to explore the interaction of various factors with data quality and their potential impact on treatment effect, and the ability to streamline the processes of data review and site selection for inspection at FDA.