Medidata Announces Launch of Medidata Detect
Medidata, a Dassault Systèmes company, announced the launch of Medidata Detect, a centralized statistical monitoring solution that aims to improve data quality and promote patient safety in clinical trials for new medicines, vaccines, and medical devices. Medidata Detect, part of Medidata’s regulatory-compliant and unified Medidata Rave Clinical Cloud platform, helps customers manage data quality, monitor site performance, and promote patient safety by uncovering and finding errors, trends, and anomalies in data through statistical algorithms and tests.
Glen de Vries, co-founder and co-CEO, Medidata said, “Detect is another example of our continuous innovation that helps advance clinical trials with increased data accuracy and speed. It’s another way we’re working to get important new vaccines and therapeutics to patients in safer, faster ways.”
A report in the Journal of the American Medical Society (JAMA)* found almost a quarter of new drug submissions required one or more resubmissions before they were approved, with a median delay to approval of 435 days following the first unsuccessful submission. Medidata Detect uses one central system for aggregation and review of any number of data sources, flagging data errors, trends, and anomalies in real time.
* Sacks LV, Shamsuddin HH, Yasinskaya YI, Bouri K, Lanthier ML, Sherman RE, “Scientific and Regulatory Reasons for Delay and Denial of FDA Approval of Initial Applications for New Drugs, 2000-2012.” JAMA.2014;311(4):378–384.
Read the full release, here.
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.
