Weill Cornell Medicine researchers have developed a machine learning model that can identify patients likely infected with SARS-CoV-2 based on routine lab tests.
The company is commercializing a genome-wide sequencing method called MRDetect, developed by researchers at the New York Genome Center and Weill Cornell Medicine.
The partners are planning to develop and commercialize UroMap, a urine-based gene-expression test for acute cellular rejection in kidney transplant recipients.
Newly discovered biomarkers of preterm birth risk — D-lactic acid and TIMP-1 — may lead to a simple ELISA test at the point of care, its developers said.
The grant recipients will receive up to $5 million each and are led by scientists at institutions including Harvard Medical School and the Cleveland Clinic.
The assay monitors mutations across a patient's genome and matches them to mutations found in a patient's resected tumor and in DNA in the bloodstream.
Groups from Austria, Spain, Germany, and the US demonstrated that the GeneReader can reliably detect cancer mutations in tissue and liquid biopsy samples.
