Thursday, May 16, 2024

GenomOncology Selected by Personalis to Support MRD and SNV Analysis for NeXT Personal Assay

GenomOncology announced that the GenomOncology (GO) Pathology Workbench has been selected by Personalis to support its NeXT Personal assay for molecular residual disease (MRD) detection.

NeXT Personal delivers industry-leading sensitivity to detect MRD and cancer recurrence at the earliest timepoints. The assay tracks and annotates individual variants over the whole evolution of a patient’s trajectory in a single panel design. Variants tracked within NeXT Personal are derived from those detected in the tissue and include those known to be associated with cancer recurrence or therapy resistance.

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Personalis selected GenomOncology to facilitate variant review, interpretation, and reporting for NeXT Personal. The GO Pathology Workbench streamlines variant analysis for all panels due to its intuitive workflow and extensive knowledge base of evidence, guideline-based therapies, and biomarker-based clinical trials, providing the insights needed for clinicians to guide patient decisions.

“The flexibility of the GO Pathology Workbench permits the efficient addition of new panels and alteration types, giving institutions the ability to continuously advance their solution or test offerings. By supporting MRD analysis with NeXT Personal, the GO Pathology Workbench aids Personalis in their case analysis by yielding the data required to identify disease progression for patients at an earlier stage of recurrence,” said Sarah Dubay, Client Services.

GenomOncology provides the healthcare community with data-driven insights to improve cancer care. GenomOncology strengthens precision oncology workflows by transforming valuable, but unusable data, into actionable oncology treatment options and strategic insights. GenomOncology’s Precision Oncology Platform (POP) powers its comprehensive set of end-to-end software solutions that enhance decision support. POP combines both proprietary content and public and licensed data sets with your internal patient data to provide you the information necessary to improve patient outcomes

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