Deep 6 AI

by Deep 6 AI  · Based in United States → — AI-powered precision research platform that uses Natural Language Processing (NLP) to mine EMR data for rapid clinical trial patient matching and RWE generation.
Cardiology Neurology Oncology

Enterprise licensing model; not publicly disclosed.

Overview

Deep 6 AI is an innovative healthcare technology company that leverages artificial intelligence (AI) to accelerate and improve clinical trial recruitment. It disrupts the clinical trial enrollment process by transforming the way researchers identify eligible patients. Using AI and natural language processing (NLP), the platform analyzes both structured and unstructured real-time clinical data from Electronic Medical Records (EMRs), including physician notes, pathology reports, genomics results, and lab reports, to precisely match eligible patients to clinical trials in minutes, not months.

The Deep 6 Precision Research Ecosystem connects healthcare organizations (HCOs), researchers, treating physicians, sponsors, and Contract Research Organizations (CROs), facilitating collaboration and advancing research. The platform is deployed enterprise-wide at health systems and is built on a secure, HIPAA-compliant cloud environment (AWS Virtual Private Cloud, Amazon EKS cluster) to ensure data security and privacy, with data ownership remaining with the healthcare organization.

Deep 6 AI was acquired by Tempus AI on March 11, 2025, expanding Tempus’s platform reach and reinforcing their shared mission of accelerating precision medicine.

Reviewed by Pouyan Golshani, MD — Interventional Radiologist

Key Features

  • AI-Powered Patient Matching
  • Natural Language Processing (NLP) on Unstructured Data
  • Real-Time EMR Data Querying
  • Clinical Trial Cohort Builder
  • Site Feasibility Assessment
  • Real-World Evidence (RWE) Generation
  • Trial Recommender for Physicians
  • Genomics Integration Module
  • EHR Integration (Epic, Cerner)
  • De-identification and security controls

Use Cases

  • Accelerate patient recruitment for clinical trials
  • De-risk trial planning and site selection
  • Generate Real-World Evidence (RWE)
  • Identify patients for precision medicine trials
  • Reduce clinical trial delays
  • Improve patient outcomes and satisfaction

What Physicians Need to Know

Clinical Trial Matching
Leverages AI and Natural Language Processing (NLP) to analyze structured and unstructured Electronic Medical Record (EMR) data, including physician notes, pathology reports, and lab results, to precisely match patients to complex clinical trial inclusion/exclusion criteria in minutes. It also supports site feasibility assessments and cohort building.
Real-World Evidence Analysis
Enables the generation of Real-World Evidence (RWE) by curating deep, real-world data (RWD) sets for prospective monitoring, registries, and RWE studies. The platform partners with entities like Graticule for enhanced RWD services.
Genomic Data Integration
Features an AI-powered genomics module launched in September 2023, which mines genomics data across EMR systems and disparate genetic reports. It uses AI to contextualize structured and unstructured genomic and phenotypical clinical data to find patients with specific genetic markers in real-time, allowing queries for over 19,000 genes and various mutation types for precision matching.
Collaboration Features
Operates as a 'Precision Research Ecosystem' designed to connect all clinical trial stakeholders, including healthcare organizations, researchers, treating physicians, sponsors, and Contract Research Organizations (CROs), facilitating shared workflows and data brokering.
Physician Tip

Physicians can utilize Deep 6 AI to rapidly identify cutting-edge treatment options for their patients by efficiently matching them to relevant clinical trials. The platform significantly reduces the manual burden of patient screening and offers a holistic view of patient data, including critical genomic information, ensuring highly precise and personalized trial matching. This enables faster access to advanced therapies and supports informed decision-making.

Deep 6 AI integrates directly with major Electronic Medical Record (EMR) systems such as Epic and Cerner, leveraging secure, normalized data pipelines. The platform is built on a secure cloud environment (AWS Virtual Private Cloud) and utilizes the Spark NLP platform for advanced text analysis. It also employs FHIR for robust data interoperability. Deep 6 AI was acquired by Tempus AI in March 2025, indicating deeper future integrations within Tempus's broader precision medicine and AI platform. Additionally, it partners with organizations like Graticule for specialized real-world data services.

Details

Category Drug Discovery & Research
Pricing Enterprise licensing model; not publicly disclosed.
  • Enterprise licensing model, typically involving annual or multi-year contracts with healthcare organizations, sponsors, and CROs
  • Pricing is customized based on the scale of deployment, data access, and services required
  • 2025 enterprise deals commonly ranged from $500,000 to several million per year depending on trial volume and platform scope
DeploymentCloud-based (AWS Virtual Private Cloud, Amazon EKS cluster), deployed enterprise-wide at health systems.
Compliance
BAA AvailableUnknown AI-estimated
HIPAA CompliantUnknown AI-estimated
FDA Status Unknown AI-estimated

Publications and case reports show that Deep 6 AI substantially accelerates and improves recruitment efficiency at health systems and research networks, but there is no evidence that the platform has been evaluated as a clinical diagnostic/therapeutic device or undergone formal clinical validation trials in that sense; validation is operational (recruitment metrics), not clinical outcome–based.

Integrations
EHR Not specified
Specialties Cardiology, Neurology, Oncology

What the Web Says

Deep 6 AI is a clinical trial acceleration software that uses artificial intelligence (AI) and natural language processing (NLP) to identify eligible patients for clinical trials. It analyzes both structured and unstructured patient data from electronic health records (EHRs), including physician notes, pathology reports, and 'omics data, to match patients to complex trial protocols in minutes rather than months. The platform aims to address the inefficiencies of traditional patient recruitment methods, which often lead to trial delays and increased costs.

Overall: Positive

Strengths

  • Accelerates patient recruitment from months to minutes.
  • Analyzes both structured and unstructured clinical data, including physician notes and pathology reports.
  • Improves precision matching of patients to complex trial criteria, reducing false positives.
  • Helps find hard-to-reach or rare disease patients.
  • Provides a self-service platform for researchers to build cohorts and refine study criteria.
  • Operates in a secure, HIPAA-compliant environment, protecting patient privacy.

Limitations

  • Predictive performance depends on the quality, completeness, and timeliness of source data.
  • Outputs are for decision support only and require validation by clinical and trial teams.
  • Integration with proprietary EHRs and other systems may require significant IT effort.
  • Regulatory, privacy, and compliance review is necessary when using AI outputs.
  • Potential for bias and representativeness issues if models are trained on under-captured populations or coding disparities.
  • Model drift and data-schema changes can affect performance.

Based on reviews from: The Silicon Review, SourceForge, pharmaphorum, Deep 6 AI: How Top Life Sciences Teams Are Slashing Trial Timelines by Months, Deep 6 and Carle Partner to Deploy Artificial Intelligence in Clinical Trials, Indeed.com, Growjo, Startup Deep 6 Lands $17 Million To Use AI To Help Find Patients For Clinical Trials, Reddit (r/ClinicalResearchAI), New Jersey Alliance for Clinical and Translational Science (NJ ACTS), Advancing Clinical Research With The Use Of Deep 6 AI, YouTube (Deep 6 AI Leverages AWS to Accelerate Clinical Trial Recruitment and Digitize Clinical Workflows), Work in progress Integrating AI-Enabled Clinical Trial Matching into Operations

Last updated: 2026-08-21

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Press & Coverage

Tempus (via Business Wire/Nasdaq)
Tempus Announces Acquisition of Deep 6 AI
Tempus AI, a technology company focused on advancing precision medicine, acquired Deep 6 AI, an AI-powered precision research platform for healthcare organizations and life sciences companies. This acquisition aims to broaden Tempus's reach and enhance its ability to deploy critical applications for patient care and clinical trials.
2025-03
PR Newswire
Deep 6 AI and Graticule Partner to Accelerate Clinical Trial Recruitment and Improve Population Health
Deep 6 AI partnered with Graticule to develop research algorithms and real-world data services for identifying and prioritizing patients for clinical trials across various disease indications. Their initial algorithm automates patient screening for a cardiovascular medical device trial, leveraging AI and natural language processing to mine structured and unstructured EMR data.
2024-01
Applied Clinical Trials Online
Deep 6 AI Launches AI-Powered Genomics Module
Deep 6 AI launched its genomics module, which uses AI to mine genomics data across electronic medical record (EMR) systems and genetic reports to find patients with specific genetic markers in real time. This allows for precision-matching patients to clinical trials based on their complete clinical and genomic profiles.
2023-09
Frontiers in Medicine
Artificial intelligence in clinical medicine: catalyzing a sustainable global healthcare paradigm
This peer-reviewed article highlights Deep 6 AI as a clinical trial recruitment platform that utilizes AI to identify eligible patients by analyzing electronic health records (EHRs) for inclusion and exclusion criteria. It positions Deep 6 AI as a tool revolutionizing patient care and medical research through AI integration.
2023-08
WCG Clinical
WCG and Deep 6 AI Announce Best-In-Class Partnership to Enable Faster, Smarter Clinical Trial Patient Recruitment
WCG and Deep 6 AI partnered to enhance targeted patient recruitment in clinical trials and accelerate enrollment in medical research. The collaboration combines WCG's market position and site-enabling capabilities with Deep 6 AI's software, which connects over 28 million patients across more than 2,000 healthcare facilities.
2022-05
pharmaphorum
Deep 6 AI: the smart software breathing new life into clinical trials
This article discusses how Deep 6 AI's platform addresses the challenge of unstructured patient data in clinical trial recruitment by using AI to pull insights from electronic medical records in minutes. The company secured $17 million in Series A funding in 2019 and has built an expansive ecosystem of hospitals and patient data.
2021-06
Business Wire
Deep 6 AI Announces Substantial Expansion of its Innovative AI-Based Clinical Trial Acceleration Software and Research Ecosystem
Deep 6 AI announced significant growth with new customer wins and an expanded executive leadership team, including Chris Brubaker as Chief Marketing and Customer Officer and Talha F. Basit as Chief Technology Officer. The company emphasizes the potential of its AI-based clinical trial acceleration software to impact patient lives.
2021-06
Technology Magazine
Deep learning in healthcare: Deep 6 AI and MIT demo uses
This article highlights Deep 6 AI's role in using deep learning and natural language processing to screen patients for clinical trials, particularly in the age of precision medicine where trial criteria are increasingly challenging. The company's method involves processing medical records to identify and label relevant criteria, leading to over 100,000 matches.
2020-05

Videos

Product demos, reviews, and walkthroughs for Deep 6 AI.

View all on YouTube

Frequently Asked Questions

Deep 6 AI leverages artificial intelligence and natural language processing to analyze both structured and unstructured electronic medical record (EMR) data, including physician notes and pathology reports. This allows it to identify eligible patients for clinical trials in minutes, significantly accelerating patient recruitment and site feasibility for drug discovery research.
Deep 6 AI is fully HIPAA-compliant and operates within a secure cloud environment, such as AWS Virtual Private Cloud. The platform includes features for data de-identification and security controls, ensuring that data ownership remains with the healthcare organization.
Yes, several alternative platforms exist, including BEKhealth, Medidata Solutions, TriNetX, and Antidote Match, among others. Deep 6 AI differentiates itself by its ability to deeply mine unstructured EMR data, such as physician notes and genomics, to create a holistic patient profile, which can uncover patients often missed by systems relying solely on coded data.
Deep 6 AI generally operates on an enterprise licensing model, involving annual or multi-year contracts with healthcare organizations, sponsors, and CROs. Specific pricing is not publicly disclosed and is customized based on the scale of deployment, data access requirements, and the services needed.
While Deep 6 AI significantly streamlines patient identification, it does not entirely eliminate the need for human oversight, as partial matches may require additional manual review. Challenges also include navigating evolving data-privacy regulations and ensuring rigorous mitigation of potential AI biases in patient matching.
Deep 6 AI integrates by connecting directly to existing EMR systems (like Epic and Cerner), allowing researchers and treating physicians to query patient data in real-time. This enables physicians to quickly identify patients who meet complex trial inclusion/exclusion criteria, reducing the manual burden of chart review and facilitating referrals to cutting-edge treatments.
Deep 6 AI analyzes a comprehensive range of patient data, including both structured and unstructured information from electronic medical records. This encompasses physician notes, pathology reports, genomics results, lab reports, and other clinical documentation, allowing it to access up to 80% more patient data than systems relying solely on coded information.

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Suggest an Edit → | Last Verified: 2026-05-21 | First Added: 2026-05-21
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