• Percepta relies on cells taken during a normal bronchoscopy
• Envisia uses patient samples that are obtained using transbronchial biopsy

Veracyte, Inc. (NASDAQ: VCYT) announced on 9/27/18 that new data highlighting the ability of the Percepta Bronchial Genomic Classifier to reduce unnecessary invasive procedures in lung cancer diagnosis will be shared in an oral presentation at CHEST 2018, the annual meeting of the American College of Chest Physicians®. In addition, new data demonstrating that the Envisia Genomic Classifier provides reliable results to help physicians more confidently diagnose interstitial lung disease (ILD), including idiopathic pulmonary fibrosis (IPF), will be highlighted in a second oral presentation at the meeting. CHEST 2018 will be held October 6-10 in San Antonio, Texas.

“These new study data supporting the Percepta and Envisia classifiers add to the growing body of evidence demonstrating that our genomic tests enable more confident diagnoses of lung cancer and ILDs, including IPF,” said Bonnie Anderson, Veracyte’s chairman and chief executive officer. “We are committed to ensuring that physicians who treat these diseases feel confident that the Percepta and Envisia classifiers will give them reliable answers to help inform accurate and timely diagnoses, without the need for surgery.”

Lung cancer and ILD/IPF are often difficult to diagnose without invasive procedures. As a result, many patients endure risky, costly diagnostic surgery that may be unnecessary; delayed and potentially inappropriate treatment; and anxiety.Percepta relies on cells taken during a normal bronchoscopy. Envisia uses patient samples that are obtained using transbronchial biopsy, a nonsurgical procedure that is commonly used in lung evaluation.

The Percepta Bronchial Genomic Classifier uses advanced genomic and machine learning technology to improve lung cancer diagnosis for patients while reducing the need for invasive procedures. The classifier is run when bronchoscopy results are inconclusive, and helps physicians determine which patients are at low or very low risk for cancer and may therefore be monitored with CT scans instead of undergoing further, invasive diagnostic procedures. The Percepta classifier uses proprietary “field of injury”-based technology to detect molecular changes in the main lung airway of current or former smokers. Percepta detects these genomic changes to determine the likelihood that a nodule is cancerous without the need to sample the nodule directly. The classifier’s performance has been validated in multiple, rigorous clinical studies, including clinical validation data published in The New England Journal of Medicine.

The Envisia Genomic Classifier is the first commercially available test to improve the diagnosis of idiopathic pulmonary fibrosis (IPF). The Envisia test enables physicians to more confidently differentiate IPF from other interstitial lung diseases (ILD), helping to guide an optimal patient treatment plan that can improve outcomes and reduce risk. The classifier works by harnessing the power of RNA sequencing and machine learning to detect a genomic pattern of usual interstitial pneumonia (UIP), whose presence is required for IPF diagnosis. The Envisia test is proven to detect UIP with high correlation to the gold standard – histopathology results read by ILD experts – without the need for surgery.