BALTIMORE and PALO ALTO, Calif., Oct. 21, 2024
Provider of Accessible Blood-Based Tests for Cancer Detection Highlights Results of Clinical Trial in Preeminent Peer-Reviewed Publication
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BALTIMORE and PALO ALTO, Calif., Oct. 21, 2024 /PRNewswire/ -- Today, DELFI Diagnostics, Inc., developer of accessible blood-based liquid biopsy tests that deliver a new way to enhance early cancer detection, is announcing the publication of a new paper, "Cancer treatment monitoring using cell-free DNA fragmentomes," in Nature Communications that demonstrates the effectiveness of cell-free DNA (cfDNA) fragmentomes as a means of assessing tumor burden for treatment response, monitoring, and clinical outcome prediction. cfDNA fragmentomes are tumor and mutation-independent, and the approach described in the paper (called DELFI-Tumor Fraction or "DELFI-TF") requires only 800ul of plasma.
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The company currently has an active pipeline of biotech and pharmaceutical companies using the DELFI-TF tumor uninformed assay for early efficacy data of developmental drugs tested in phase I and II clinical trials. In February of this year, DELFI announced a DELFI-TF RUO partnership with Immunocore. This study details the DELFI-TF development and its independent validation.
"We have a vision of the future where cancer is routinely detected early, and patients have more options and better outcomes as a result. We are excited to share this important new application of our proprietary whole genome fragmentomics technology to monitor therapy response with a simple blood test at a breakthrough cost structure," said Susan Tousi, CEO of DELFI Diagnostics.
DELFI's flagship product, FirstLook Lung, was commercialized last year and is a simple blood-based test that provides health systems and their clinical operations with a solution that can be offered to screen eligible patients during a routine visit. Lung cancer remains the biggest cancer killer and still accounts for 1 in 5 cancer-related deaths in the U.S. Moreover, 94% of eligible U.S. adults aren't currently being screened for lung cancer. Both FirstLook Lung and DELFI-TF provide decision-making support for providers whose mission is to detect, treat, and monitor patients at risk for lung cancer.
The new paper further demonstrates the characteristics of DELFI-TF in two independent validation cohorts. "DELFI-TF is a locked machine learning classifier validated in two independent cohorts of colorectal and lung cancer patients and can detect clinical outcomes earlier than imaging. This work demonstrates the potential of DELFI-TF to estimate tumor burden for accurate treatment-response monitoring and clinical outcome prediction," added Lorenzo Rinaldi, PhD and Head of Translational Science at DELFI.
About DELFI DiagnosticsDELFI Diagnostics is developing next-generation, blood-based tests that are accurate, accessible, and deliver a new way to help detect cancer. DELFI tests are built to solve the highest-burden population health issues, including in historically underserved demographics, and have the potential to save lives on a global scale. FirstLook Lung, for individuals eligible for lung cancer screening, is our first laboratory-developed screening test and requires a simple blood draw that can be incorporated with routine blood work. The test is based on fragmentomics, the discovery that cancer cells are more chaotic than normal cells and, when they die, leave behind tell-tale patterns and characteristics of cell-free DNA (cfDNA) fragments in the blood. The DELFI platform applies advanced machine-learning technology to whole-genome sequencing data to assess individuals' cfDNA fragments against populations with and without cancer. FirstLook Lung uses these millions of data points to reliably identify individuals who may have cancer detected through low-dose CT, including early-stage disease, with a negative predictive value of 99.8 percent. This test has not been cleared or approved by the FDA. To learn more about the FirstLook Lung test, visit www.delfidiagnostics.com or www.firstlooktest.com.
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SOURCE DELFI Diagnostics