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Quri brings to you a cutting-edge AI engine that screens through EMR patient databases, conducts deep analysis on each patient to see if they match extensive study criteria, and uncovers the list of highly-qualified candidates.Clinical trials serve as the critical bridge between groundbreaking therapies and the patients who need them most. However, this bridge is plagued by a significant bottleneck: Close to 50% of the 500,000 clinical trials initiated each year do not achieve their participant enrollment goals. This not only escalates costs but also delays. Adding to this challenge is the stark reality that a mere 3% of US patients who are eligible for trials manage to successfully find them. This situation not only escalates costs and delays for sponsors, but also drastically hinders patients' access to potential new treatments.
The heart of the issue lies in the unique and intricate eligibility criteria each trial sets forth—criteria buried within complex medical terminology that makes finding an eligible patient a daunting task. Clinical researchers must perform an arduous and manual process of reviewing a potential candidate’s medical data to determine if they qualify based on the study’s criteria.
Principal Investigators typically have a vast patient database of thousands and thousands of records. Referring their patients to their associated clinical trials is a key recruitment source. However, the complexity of each trial's eligibility criteria makes it nearly impossible for them to remember every patient in their database who may be eligible. Moreover, it is not feasible for them to manually search their entire patient database for potential candidates. In this haystack of patients, there are numerous "needles" or qualified candidates that are being entirely overlooked and missed.
Quri aims to completely eradicate this issue by automating the candidate identification and screening through the use of of advanced LLM models, renowned for their reasoning capabilities and ability to digest large quantities of data. Quri has put together a suite of fine-tuned AI models bundled in a HIPAA compliant environment that can understand medical concepts and a study protocol. The AI then applies reason over a patient’s medical information to determine if the patient is a match, or not. With this, sites can automatically find protocol-eligible candidates from an EMR. The AI-powered screening through the physician’s EMR immediately identifies all the candidates that match your trial’s complex criteria.
How the “EMR Precision Scout: AI-Driven Candidate Finder” Works:
Connect your EMR: Securely link your EMR system to Quri with guided setup from our team.
Set-Up Your Screening Parameters: Choose up to three levels of patient matching, from basic indications to full I/E criteria for more qualified patient
AI Batch Analysis: Quri analyzes all medical records, including unstructured notes, to find matches against your parameters
Matched Patient Report: Receive a report summarizing the number of patients matching your selected criteria. Unlock it to access the detailed list of matched patients
The results are significant...
10X Participant Discovery: Unveil up to ten times more eligible participants, halving the time to full enrollment.
4x Revenue: Enrolling more high-quality candidates boosts study profitibility and performance.
While this groundbreaking technology has been successfully implemented in case studies and at large research institutions, Quri's mission is to make it accessible to all sites, regardless of their size or resources. This commitment to support research sites is ingrained in our DNA, with the company founded by independent research sites. Our goal is to enable all sites with the benefit of advanced innovations and to accelerate the pace of clinical trials and bring potential new treatments to patients more rapidly.
Let’s get started today, EMR Precision Scout: AI-Driven Candidate Finder is free to try!
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