Empowering the most precise treatment.
Strikingly fast.
Speeding patients to trials.

By identifying patients at the time of diagnosis, our advanced AI-enabled patient recruitment platform compresses study timelines by finding the best-suited patients for clinical trials.

Deep Lens gives you

a sharp focus on patients

Our AI-driven cloud platform, VIPER, identifies and recruits patients earlier than current methods, at the time of diagnosis, thereby accelerating trial recruitment and bringing game-changing therapies to market sooner.

VIPER – it simply works

Cloud-based for quick and easy set up at all your participating sites.

Real-time dashboard capabilities to track site level trial performance.

Visible indicators when new patient data is received – intuitive data filters to prioritize patients who require action.

Patient data filtering to match cases against inclusion and exclusion criteria.

Molecular/genetic testing notifications to increase the number of qualified patients.

Eligibility and consent status to monitor patient enrollment.

Role-based alerting and messaging that is flexible and dynamic.

VIPER Benefits

Accelerate study timelines by identifying and recruiting patients upstream of all current methods (at the time of diagnosis).

Seamless data integration with anytime, anywhere access through the cloud.

Strengthen collaboration on groundbreaking cancer research.

Improve patient engagement to recruit patients to trials before commencing a competing therapy.

Manage patients from identification through to qualified enrollment.

Increase recruitment by community oncologists and improve the number of qualified patients who receive molecular tests.

 

Abstract #2052: Novel artificial intelligence (AI)-based technology to improve oncology clinical trial fulfillment

Authors: TJ Bowen, Laura Stephens, Mark Vance, Yancui Huang, Deborah Fridman, Chadi Nabhan

Background:

  • Less than 5% of US adult cancer pts are enrolled on clinical trials. Challenges in clinical trial fulfillment limit available treatment options, slow enrollment and ultimately delay new therapies from reaching market.
  • Patient screening requires multiple clinical team members to find pts that meet strict inclusion/exclusion criteria.
  • We evaluated the impact of new technology, Deep Lens VIPER, in identifying more qualified pts for clinical studies, and reduction of staff burden.

Methods:

  • 1 novice clinical research coordinator pre-screened 20 studies previously managed by 6 staff
  • 4 months of retrospective data triaged in 3 weeks
  • 150 previously unidentified potential patients for 16 out of 20 studies were identified
  • 11 different tumor types included in analysis across 12 biomarkers (HER2, HER4, EGFR, MET, RET, MTC, ATM, ALK, ROS1, PD-1, RAS, and MSI high)
  • 3 basket studies (multi-arm; multi-indication) were analyzed

An AI-based platform, VIPER, triaged study participants across 20 different cancer studies simultaneously, allowing identification of patients for interventional studies (previously not attempted at hospital due to resource constraints). 150 patients were identified for potential fit that were previously not identified over a four-month period.

Copies of this poster obtained through Quick Response (QR) Code are for personal use only and may not be reproduced without permission from ASCO and the authors of this paper.

VIPER identified 1,045 pts (18.3%) with malignant neoplasms that would qualify for further analysis for clinical trials enrollment. Further triage based on inclusion and exclusion criteria led to the identification of 150 previously unidentified pts for 16 of the 20 studies. The VIPER system increased monthly candidate pt catchment for 16 of the 20 studies under investigation, which is approximately 600 patients annually added for final triage for studies being conducted.

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New Jersey 07046
Phone Number: 973.316.1701
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Mountain Lakes
New Jersey, 07046
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Phone Number: 973.267.9543
Office hours:

Simon Cancer Center, Morristown Memorial Hospital
100 Madison Avenue, Suite 3402
Morristown, NJ 07962
973.316.1701