FDA Expands AI Use in Trials with CluePoints Software

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The Food and Drug Administration (FDA) has signed a new three-year Cooperative Research and Development Agreement with CluePoints, a leading provider of statistical and AI-driven software solutions, to assess data quality using statistical modeling and machine learning techniques.

The FDA is extending its use of CluePoints to include artificial intelligence and machine learning within an automated system for assessing data quality in multicenter clinical trials. This collaboration stems from a shared goal between the FDA and stakeholders to ensure the integrity of clinical trial data and the safety of participants involved in research.

Clinical research misconduct, such as the fabrication or omission of data in reporting study results, poses significant risks to trial participants and undermines the FDA’s mission to promote public health. To identify potential misconduct, the FDA relies on various methods, including site inspections and whistleblower reports. However, due to the vast number of product filings, the FDA can only inspect a small fraction of clinical trial sites.

Under the original Cooperative Research and Development Agreement (CRADA) between the FDA and CluePoints, software was developed to generate a ranked list of anomalous sites, aiding FDA inspectors in prioritizing site inspections. Key enhancements included deploying the CluePoints software in the FDA’s high-performance computing environment, developing new statistical tests for detecting anomalies, and improving the site ranking algorithm.

The new CRADA will focus on two primary objectives:

1. Enhancing the CluePoints SMART™ software to address a broader range of regulatory issues, leveraging date/time data, and incorporating AI/ML algorithms for improved anomaly detection.
2. Adapting the software to better support FDA processes related to anomaly detection, review, follow-up, and site selection for inspections.

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The anticipated benefits for the FDA include improved detection of anomalous sites, exploration of factors influencing data quality and treatment effects, and streamlined processes for data review and site selection. This collaboration underscores the commitment of both the FDA and CluePoints to advancing data quality oversight in clinical trials for the benefit of public health.

For more information on the new CRADA between CluePoints and the FDA, visit www.cluepoints.com.

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Kunal Joshi
Kunal Joshi
Meet Kunal, our insightful writer and manager for the Machine Learning category. Kunal's expertise in machine learning algorithms and applications allows him to provide a deep understanding of this dynamic field. Through his articles, he explores the latest trends, algorithms, and real-world applications of machine learning, making it accessible to all.

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