Deep Lens

by Paradigm Health  · Based in United States → — Clinical Research, Re-Engineered for Impact
Oncology
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Regulatory Status Disclosed

Overview

Paradigm Health, which acquired Deep Lens, offers an AI-powered cloud platform designed to revolutionize clinical trial matching, particularly for oncology patients. The platform seamlessly integrates diverse patient data from Electronic Medical Records (EMRs), laboratory results, and genomics to automate and accelerate the identification and enrollment of eligible patients into clinical trials. By embedding AI-native, point-of-care technology directly within healthcare provider workflows, Paradigm Health aims to make clinical research more accessible and efficient for patients, providers, and trial sponsors. This approach helps to streamline study execution, reduce administrative burden on research sites, and improve the quality and speed of data collection through features like EHR-to-EDC connectivity and automated eCRF population (eSource). The platform supports the entire clinical trial journey, from trial design and protocol optimization to feasibility, site selection, and post-approval evidence generation.

Reviewed by Pouyan Golshani, MD — Interventional Radiologist

Key Features

  • AI-powered clinical trial matching
  • Integration with EMRs, labs, and genomics data
  • Automated patient identification and enrollment acceleration
  • Streamlined study execution workflows
  • EHR-to-EDC connectivity and automated eCRF population (eSource)
  • Trial design and protocol optimization support
  • Feasibility and site selection capabilities
  • Real-time performance evaluation of trials
  • Post-approval and late-stage clinical evidence generation (SPIRE)
  • Network of community and academic research sites

Use Cases

  • Accelerating oncology clinical trial enrollment
  • Optimizing clinical trial operations for sponsors
  • Expanding patient access to clinical trials
  • Reducing administrative burden for research sites
  • Generating high-quality real-world evidence
  • Improving data quality and compliance in clinical trials

What Physicians Need to Know

Clinical Trial Matching
Deep Lens specializes in AI-driven patient-to-trial matching, significantly improving the efficiency and accuracy of identifying eligible patients for oncology clinical trials. It leverages complex eligibility criteria against detailed patient characteristics, including clinical and genomic data, to streamline the enrollment process.
Real-World Evidence Analysis
The platform utilizes real-world data (RWD) to enhance patient identification and optimize clinical trial design. By analyzing RWD, Deep Lens can gain insights into how interventions perform in diverse populations, contributing to more effective trial recruitment strategies.
Genomic Data Integration
Deep Lens integrates genomic data to enable precise patient stratification and personalized trial matching, which is crucial in oncology. This capability allows for a more targeted approach to finding patients who meet specific genetic criteria for advanced therapies.
Collaboration Features
The platform likely includes features that facilitate collaboration among clinical teams, enabling efficient communication and coordination for patient referrals and trial management. This ensures that relevant stakeholders can work together seamlessly to manage the trial matching workflow.
Physician Tip

For physicians utilizing Deep Lens, it is recommended to regularly update patient electronic health records (EHRs) with comprehensive and accurate clinical and genomic data to maximize the system's matching capabilities. Engage actively with the platform's insights to identify potential trial candidates efficiently and discuss these opportunities with patients, emphasizing the personalized treatment avenues clinical trials can offer. Leverage the system to stay informed about a broader range of available trials, potentially expanding options for patients beyond local institutional offerings.

Deep Lens's effectiveness is significantly enhanced through robust integrations with existing healthcare IT infrastructure, particularly Electronic Health Record (EHR) systems. Seamless data exchange with EHRs is critical for real-time patient data ingestion and accurate clinical trial matching. Further integrations with laboratory information systems (LIS) for genomic data and potentially with clinical trial management systems (CTMS) could optimize workflows and provide a more unified view of patient and trial information.

Details

Category Drug Discovery & Research, Oncology AI
Pricing Contact for pricing
  • Custom pricing based on organizational and trial needs; healthcare providers use the technology free of charge, with pharmaceutical companies being charged for patient identification and trial administration
DeploymentCloud platform
Compliance
BAA Available Yes AI-estimated
HIPAA Compliant Yes AI-estimated
FDA Status Not applicable AI-estimated

FDA clearance is not applicable for a clinical trial matching and management platform, as it is not a medical device or diagnostic tool.
Integrations
EHR Not specified
Specialties Oncology

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Press & Coverage

Tamarind Hill
Deep Lens Acquired by Paradigm
Deep Lens, known for its Viper software that analyzes cancer pathology and genetic data to match patients with clinical trials, has been acquired by Paradigm. This acquisition aims to further integrate clinical trials as a care option for all patients.
2024-09
Precision for Medicine
Deep Lens Announces Launch of Real Time Feasibility Offering to Assist in Oncology Clinical Trial Design and Site Selection
Deep Lens launched its Real Time Feasibility offering, a HIPAA-compliant tool that uses AI to identify eligible patients and select effective sites within the Deep Lens Unity Network for oncology clinical trials. This solution leverages their VIPER software and integrated workflows to combine EMR, lab, and genomic data.
2021-12
Business Wire
New AI-Based Clinical Trial Matching Solution, Deep Lensu2019 Viperu2122, Expanding Offering to Cancer Patients at Norton Healthcare
Deep Lens announced a collaboration to integrate its AI-based clinical trial screening and matching solution, VIPER, into cancer research at Norton Cancer Institute. VIPER automates the screening process and matches patients to trials using genomic, EMR, and pathology data.
2021-06
BioSpace
Deep Lens First to Integrate Cancer Genetic Data into AI Platform to Rapidly Match Patients to Precision Therapies and Clinical Trials
Deep Lens integrated proprietary molecular data parsing and management technology into its VIPER platform, enabling immediate and automatic matching of cancer patients to precision therapies and oncology clinical trials based on their genetic profiles.
2020-05
BioSpace
PRA Health Sciences and Deep Lens announce strategic relationship to accelerate patient recruitment for precision cancer trials
PRA Health Sciences and Deep Lens formed a strategic relationship to accelerate patient access and recruitment for oncology clinical trials. Their combined effort leverages AI and machine learning via the VIPER platform to improve identification, screening, and matching of cancer patients to precision-based trials.
2020-09
Becker's Hospital Review
Deep Lens raises $14M for AI-powered clinical trial recruitment
Deep Lens secured $14 million in funding to expand its AI platform, VIPER, for recruiting clinical trial participants. The platform combines deep learning with pathology workflows to identify trial-eligible patients at the time of diagnosis.
2019-04
pharmaphorum
Deep Lens unveils cancer diagnosis AI tech for pathologists
Deep Lens launched an AI platform called VIPER (Virtual Imaging for Pathology Education and Research) to help pathologists diagnose cancer more swiftly and accurately. The platform uses AI for diagnostic tests and can help match patients with relevant clinical trials.
2018-10
Ophthalmology
DeepLensNet: deep learning automated diagnosis and quantitative classification of cataract type and severity
A study published in Ophthalmology describes DeepLensNet, a deep learning system developed by Deep Lens, that can automatically and quantitatively classify cataract severity. The system showed superior accuracy to ophthalmologists for nuclear sclerosis and cortical lens opacity types.
2022-05

Videos

Product demos, reviews, and walkthroughs for Deep Lens.

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Frequently Asked Questions

Deep Lens's VIPER platform utilizes AI to integrate lab, EMR, and genomic data, enabling physicians to swiftly identify and match cancer patients to suitable clinical trials and precision therapies at the time of diagnosis. This streamlines the recruitment process for oncology trials and helps connect patients with advanced clinical research opportunities.
Yes, Deep Lens is designed to be HIPAA-compliant, ensuring the security and privacy of protected health information. The company has actively built a robust security and privacy program to meet these regulatory requirements.
While Deep Lens aims to improve efficiency, its effectiveness relies on seamless integration with existing EMR, lab, and genomic data systems, which can sometimes present interoperability challenges. The platform's primary focus is on oncology clinical trial recruitment, so its utility may be limited outside this specific area.
Yes, several other companies offer AI-powered solutions for clinical trial management and digital pathology. Competitors and alternatives include platforms like Valar Labs, Genospace, ClinCapture, Deep 6 AI, and Inspirata, which also focus on various aspects of clinical research and data analysis.
Deep Lens charges institutions and companies a subscription fee for the use of its VIPER platform. However, it is offered free of charge to individual pathologists and pathology groups.
Deep Lens' VIPER platform is designed to integrate directly with various EMR systems, such as Epic Records, and molecular data feeds from providers like Foundation Medicine, Caris Life Sciences, Tempus, and Guardant Health. This integration allows for automated identification of qualified patients for clinical trials by combining diverse data sources.
Deep Lens leverages proprietary AI-based trial matching solutions to provide real-time, continuously updated patient insights for faster and more accurate clinical trial enrollment. While specific validation metrics are not detailed in public information, the platform aims to significantly improve upon traditional manual methods by identifying eligible patients at the time of diagnosis.

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Suggest an Edit → | Last Verified: 2026-04-22 | First Added: 2026-04-22
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