Clinical trial enrollment does not fail because of a lack of studies. It fails when patient identification and coordination remain fragmented across clinical care and research teams.
Azra AI embeds clinical trial eligibility identification and enrollment workflows directly within clinical care, enabling scalable, enterprise clinical trial performance across the health system.
Health systems using Azra have demonstrated measurable enterprise impact, including 58% improvements in patient retention and faster time-to-treatment across care programs.
Most clinical research programs rely on processes that were never designed to scale.
Manual chart review to identify potential trial candidates
Disconnected feasibility assessments
Trial candidates discovered late in the care journey
Enrollment dependent on individual coordinator vigilance
Limited visibility into enrollment performance across sites
Clinical Trial Management Systems (CTMS) track enrolled patients. But the upstream processes required to identify eligible patients and assess feasibility often remain manual, limiting enrollment performance and scalability.
Azra enables research teams to manage clinical trials as an integrated enterprise capability, helping research programs choose the right studies, identify eligible patients, and monitor enrollment performance.
Before accepting a new protocol, research leaders need to understand whether their patient population can realistically support enrollment targets.
Azra enables automated trial pre-screening, allowing research teams to know, close to real time and with high precision, which patients may be eligible for actively recruiting trials.
This eliminates manual chart review and dramatically increases the efficiency of patient identification.
Azra provides consolidated reporting across trials, enabling research teams to:
Schedule a Clinical Trials Strategy Review to explore how Azra helps research teams identify eligible patients earlier, improve enrollment performance, and scale clinical trial programs.