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Veracyte Announces New Preliminary Data for Its In-Development Lung Cancer Portfolio Tests
Data on Noninvasive Nasal Swab Test and Percepta Genomic Atlas Presented Today at Virtual Lung Cancer R&D Day SOUTH SAN FRANCISCO, Calif.--(BUSINESS WIRE)--
About this update from Veracyte, Inc.
[{"type":"text","content":"\nData on Noninvasive Nasal Swab Test and Percepta Genomic Atlas Presented Today at Virtual Lung Cancer R&D Day\n\n SOUTH SAN FRANCISCO, Calif.--(BUSINESS WIRE)--\n\nVeracyte, Inc. (Nasdaq: VCYT) announced new preliminary performance data for its noninvasive nasal swab test for early lung cancer detection and its Percepta Genomic Atlas for informing treatment decisions at the time of diagnosis. Both tests are in development and scheduled to launch in the second half of 2021 as part of Veracyte’s comprehensive portfolio of genomic tests in lung cancer. The data were shared during the company’s Virtual Lung Cancer R&D Day, which was held today.\n\n“We are excited to bring forward novel tests that we believe will address significant unmet needs throughout the patient journey in lung cancer,” said Bonnie Anderson, Veracyte’s chairman and chief executive officer. “The preliminary data we presented today give us further confidence that our expanding portfolio of tests will improve the lives of patients through earlier diagnosis and comprehensive genomic profiling. This progress, on the heels of our expanded collaboration with the Lung Cancer Initiative at Johnson & Johnson, underscores our deep commitment to fighting this devastating disease.”\n\nVeracyte’s noninvasive nasal swab test is being developed to help physicians determine next steps for lung nodules found on CT imaging. Lung nodules identified as high risk for cancer warrant a diagnostic work-up to enable immediate treatment, while nodules identified as low risk may avoid unnecessary invasive procedures and be monitored with surveillance.\n\nVeracyte’s chief scientific officer and chief medical officer, Giulia C. Kennedy, Ph.D., shared cross-validation data for four genomic test models, which are precursors to the final test. The models were all developed using RNA whole-transcriptome sequencing data from nasal samples of patients with lung nodules, which was combined with machine learning to classify patient nodules as high or low risk for cancer. Among the four models, 44-60 percent of the truly malignant nodules were classified as high risk with a range of specificity of 90-91 percent, and 39-57 percent of the truly benign nodules were identified as low risk, with a range of sensitivity of 90-94 percent.\n\n“We are pleased with these preliminary findings, which suggest th...