DEEPGEN™ Pharmaceutical
R&D Solution

A turnkey liquid biopsy solution for oncology R&D that combines Deep Genomic with AI to achieve single-molecule precision.
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Fast-track Your Research

DEEPGEN is a new option for pharmaceutical and biotech companies and their research partners for conducting liquid-biopsy-based research to investigate somatic mutational patterns specifically focused on the biomarker of cell-free DNA (cfDNA).

DEEPGEN utilizes the most advanced sequencing technology to identify cfDNA, and it uses proprietary software and pattern recognition technology to associate patterns with disease.


With DEEPGEN, deep genomic sequencing in combination with AI pattern recognition presents several critical advantages: 

A turnkey solution: A validated platform allows users to send in blood samples and receive results within 14 days with little to no setup time 

Single molecule precision: Single molecules of cancer can bedetected more accurately and quickly

New gene association and mutational pattern detection: Technologycan help identify new genes and patterns of association that result in cancermutations 

Ultra-deep data: Profiles the mutational patterns in every single copy of DNA with 100,000X depth across 70 locations and 258 genes known to be important in cancer. The limit of detection, including technical sensitivity and specificity, is validated at 1/1000 genome copies, better than any other peer-reviewed technology to date

Representation of entire tumor: cfDNA is a representative collectionof tumor derived DNA so it can be used to circumvent tumor heterogeneity whichcan lead to inaccurate tumor diagnosis from different biopsy sites

Markers of recurrence: Currently, many tumors do not have a good biomarker to detect progression or recurrence.  Even those available such as CA125 and PSA may not be accurate in detecting response or recurrence

Non-invasive: No surgical sample needed and cfDNA can evaluate patients where surgery is not an option


DEEPGEN™ R&D Solution

Fast-track your liquid biopsy research with a solution specifically designed for deep genomic and AI data exploration.
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A turnkey liquid biopsy research solutiono

New advancements in liquid biopsy and cfDNA sequencing combined with AI can help pharmaceutical companies and their research partners:


0.1% validated MAF

Detecting a single mutant copy in a thousand wild type copies of background


Over 200 billion NGS reads to-date in clinical liquid biopsy trials

The 4 steps of the DEepgen Solutiono

Combine any or all steps to fast-track your research


Ultra-deep sequencing allows detection of extremely rare mutational events that may be indicative of disease presence or recurrence. DEEPGEN utilizes the most advanced techniques to ensure that data output is the highest possible quality. DEEPGEN’s NGS process is outlined below:

  • Receive standard blood sample (10-20ml)
  • Nucleic acid extraction using the Qiagen QIAsymphony and an innovative extraction technology based on industry leading chemistry that achieves high efficiencies from standard input volumes of blood
  • Run DEEPGEN assay on Illumina NovaSeq 6000

The DEEPGEN panel is unique in that the assay design provides both industry leading technical sensitivity and specificity in a large pan-cancer detection custom designed panel. The assay is comprised of a target panel of 258 genes identified to be related to cancer - through a proprietary machine learning algorithm. DEEPGEN ensures industry leading analytical and clinical performance. A combination of both proprietary and consensus markers, the panel contains genes in the U.S. National Comprehensive Cancer Network (NCCN) Guidelines, lung cancer and colorectal cancer (CRC), and emerging cancer biomarkers. DEEPGEN achieves a true limit of detection of 1/1000 genome copies, better than any other available technology to date.

Technologies Used: Illumina NovaSeq 6000, Qiagen QIAsymphony, DEEPGEN custom assay

Output: FastQFiles

2 Deepgen mutational Detection

Using ultra-deep sequencing and proprietary analyses, extremely low level mutations can be detected and separated from the background noise of random mutations. Each base is evaluated to determine true pathogenic mutations from those that are nonpathogenic or due to sequencing errors.

Technologies Used: DEEPGEN core engine (Deep signal processing, noise reduction, error correction, machine learning and cloud enabled bioinformatics system)

Output: Mutational Patterns

3 DEEPGEN AI disease Recognition

DEEPGEN AI disease recognition technology utilizes both classical machine learning, and deep learning layers that have the ability to recognize relationalpatterns between individual features that correlate with certain disease profiles. DEEPGEN covers 15 cancer types including breast, colorectal, lung, ovarian, prostate, and more. This machine learning and AI infrastructure is what ultimately determines disease profiles in clinical samples that can then be used for multiple applications ranging from drug development to more general healthcare solutions.

Technologies Used: Deep learning networks, DEEPGEN disease data sets from clinical trials

Output: Disease patterns and detection diagnostics

4 DEEPGEN Analytics

DEEPGEN analytics allows the user to understand mutational patterns by gene summaries, gene profiles including onco and tumor suppressor gene descriptions for mutations that were contained in the sample, as well as detected mutational targets that are FDA approved for guiding treatment decisions. DEEPGEN analytics also provides quality control tools that allow sample quality variables such as cfDNA input levels, plasma volumes, sequencing depth and total DNA copy counts by targets and amplicons. Additionally, easy overviews over clinical data allows for correlation between genomic and laboratory findings with clinical and demographic variables such as age, gender, ethnicity as well as comorbidities and diagnoses.


Contact our Team

William Ricketts, PhD/ Director of Clinical Affairs

William Ricketts, PhD is the Director of Clinical Affairs at Quantgene and is responsible for developing studies to validate new products and identifying areas of unmet medical need.

Dr. Ricketts has been in diagnostic development for more than fifteen years. He has designed, developed, and launched several CLIA cleared tests for cancer and autoimmune disease. In this role, he has written protocols and worked extensively with physicians to validate new tests and technologies for use in the clinical laboratory.

Dr. Ricketts received his BA from the University of Virginia and his PhD from the University of CA-San Diego. He is currently a Society of Gynecologic Oncology member and the American Association of Cancer Researchers.

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