Data MATRIX Introduces AI-operated Patient Survival Assessment Tool
A feature of the presented tool for predictive analysis of Real-World Data (RWD) is the ability to collect and analyze data on different patient cohorts. Machine algorithms collect information about patients from medical records received from prevention and treatment facilities, pharmaceutical companies, and researchers in 29 regions of the Russian Federation.
As a result, pharmaceutical and biotech companies will have a legally compliant provider of RWD derived from millions of EHRs. This will aim to contribute to the overall knowledge base on drugs efficacy and safety, including those of vaccines.
Driving Diversity with the Integrated Research Model
October 16th 2024Ashley Moultrie, CCRP, senior director, DEI & community engagement, Javara discusses current trends and challenges with achieving greater diversity in clinical trials, how integrated research organizations are bringing care directly to patients, and more.
AI in Clinical Trials: A Long, But Promising Road Ahead
May 29th 2024Stephen Pyke, chief clinical data and digital officer, Parexel, discusses how AI can be used in clinical trials to streamline operational processes, the importance of collaboration and data sharing in advancing the use of technology, and more.
The Rise of Predictive Engagement Tools in Clinical Trials
November 22nd 2024Patient attrition can be a significant barrier to the success of a randomized controlled trial (RCT). Today, with the help of AI-powered predictive engagement tools, clinical study managers are finding ways to proactively reduce attrition rates in RCTs, and increase the effectiveness of their trial. In this guide, we look at the role AI-powered patient engagement tools play in clinical research, from the problems they’re being used to solve to the areas and indications in which they’re being deployed.
