Cofactor Genomics, Inc. has announced the validation and launch of OncoPrism-NSCLC, an RNA-based diagnostic test designed to predict the response of non-small cell lung cancer (NSCLC) patients to immune checkpoint inhibitors (ICI). This development follows the recent announcement of Medicare coverage for Cofactor’s OncoPrism-HNSCC test, marking a significant expansion in the application of the company's RNA-based diagnostic technology.
OncoPrism-NSCLC leverages Cofactor’s Health Expression Models, which combine RNA expression data with machine learning algorithms to forecast patient response to ICI therapy. According to Dr. Jarret Glasscock, CEO of Cofactor Genomics, the launch of OncoPrism-NSCLC is a crucial step in bringing precision medicine to a larger population of cancer patients, particularly those with NSCLC, who represent a substantial portion of individuals undergoing ICI treatment.
Clinical Validation and Trial Data
The validation of OncoPrism-NSCLC is based on data from patients across 12 clinical sites participating in the PREDAPT trial (NCT04510129). The test utilizes pre-treatment tumor biopsies to predict response to ICI and is processed in Cofactor’s CAP-accredited, CLIA-certified laboratory. Results from the PREDAPT trial demonstrated a significant correlation between OncoPrism-NSCLC predictions and actual patient response to ICI, both as a single agent and in combination with chemotherapy.
Expanding Applications
In addition to NSCLC and HNSCC, Cofactor’s PREDAPT clinical trial is actively evaluating the utility of OncoPrism in nine other cancer types. These include colorectal, breast, cervical, liver, kidney, esophageal, and bladder cancers, indicating a broad potential for the application of Cofactor’s RNA-based diagnostic approach.
About Cofactor Genomics
Cofactor Genomics is focused on bridging the precision medicine gap by utilizing RNA to address critical challenges in healthcare. The company’s patented Health Expression Models (HEMs) analyze billions of biological RNA data points to create high-dimensional models of disease, biology, and therapy response. Cofactor's work has been published in journals such as The Journal of ImmunoTherapy of Cancer and The Journal of Molecular Diagnostics.
