Viz.ai to Expedite Patient Enrollment in NIH-funded PE-TRACT Clinical Trial
Viz.ai, the leader in AI-powered disease detection and care coordination, today announced it will use its VizTM RECRUIT platform to optimize patient enrollment for the NIH-funded1 Pulmonary Embolism—Thrombus Removal with Catheter-Directed Thrombolysis (PE-TRACT) clinical trial. The PE-TRACT trial will be the most rigorous randomized controlled clinical trial to date of catheter-directed therapy for pulmonary embolism, with plans to enroll 500 patients across 30-50 sites.
The PE-TRACT trial is designed to address whether catheter therapy should be routinely used to treat intermediate-risk pulmonary embolism versus anticoagulants alone. Pulmonary embolism occurs when a blood clot is trapped in an artery in the lung, blocking blood flow to part of the lung.
“The PE-TRACT trial will offer a deeper knowledge of pulmonary embolism by providing a comprehensive comparison of catheter-directed therapy plus anticoagulation to anticoagulation alone,” said Dr. Akhilesh Sista, [Principal Investigator of the PE-TRACT trial, Interventional Radiologist and Faculty, Weill Cornell Medical College]. “PE-TRACT will provide valuable insights to patients and providers regarding which approach best maintains cardiopulmonary health in the year following PE. Viz.ai’s RECRUIT tool has the potential to efficiently identify potential participants and help this important trial complete enrollment on time.”
Participating research institutions in the PE-TRACT trial will use Viz RECRUIT to find, screen, and enroll clinical trial candidates. Viz RECRUIT, an AI-powered clinical trial enrollment platform, automates the identification and triage of eligible candidates for pre-trial review, while reducing the burden on the research team. Using Viz RECRUIT, sites will be able to automatically screen patients based on pulmonary embolism and high right ventricular to left ventricular diameter (RV/LV) ratio. The cloud-based technology helps to broaden the recruitment funnel in both size and diversity and streamlines the trial enrollment workflow. To date, Viz RECRUIT has been used to screen nearly 300,000 patients and identify over 14,000 clinical trial candidates across 100 healthcare facilities.
“We’re honored to be the partner of choice for this clinical trial to accelerate vascular research using Viz RECRUIT. With our platform’s real-world accuracy and demonstrated success, researchers can use AI to identify potentially eligible trial candidates, regardless of their location, ultimately expediting the clinical trial enrollment process,” said Jayme Strauss, chief clinical officer, Viz.ai. “We aim to expand the participation and diversity of participants in clinical research to make treatments safer for all patients and advance the development of novel treatments, while empowering research teams to efficiently and consistently screen for patients and coordinate research.”
Information on the PE-TRACT trial and the Viz RECRUIT platform will be presented at the upcoming Society of Interventional Radiology Meeting on March 7 in Phoenix, Arizona. To learn more, please visit the Viz.ai website.
1 The study was funded by the National Heart, Lung, and Blood Institute, of the National Institutes of Health, under grant award number 1UG3HL155798-01A1. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
About Viz.ai, Inc.
Viz.ai is the pioneer in the use of AI algorithms and machine learning to increase access to life-saving treatments, covering more than 200 million lives across 1,300+ hospitals and health systems in the U.S. and Europe. The AI-powered Viz Platform is an intelligent care coordination solution that identifies more patients, informs critical decisions at the point of care, and optimizes care pathways and helps improve outcomes. Backed by real-world clinical evidence, the Viz Platform delivers significant value to patients, providers, and pharmaceutical and medical device companies. For more information visit viz.ai.
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