Veracyte Launches Early Access Program for Envisia Genomic Classifier Test to Improve IPF Diagnosis
Veracyte, a leading genomic diagnostics company, launched an Early Access Program to make its Envisia Genomic Classifier test available for idiopathic pulmonary fibrosis (IPF) patients, the company announced.
Envisia Genomic Classifier was designed to improve the diagnosis of IPF and help ensure an appropriate treatment without requiring surgery.
The program’s first participants include physicians from Jefferson (Philadelphia University + Thomas Jefferson University), University of California, Los Angeles (UCLA), Providence Sacred Heart Medical Center in Washington state, and Keck Medicine of University of Southern California, who are offering patients the genomic test.
“Multiple studies have demonstrated that the Envisia Genomic Classifier supports confident IPF diagnosis and optimal patient management,” Bonnie Anderson, Veracyte’s chairman and CEO, said in a press release.
“We are honored to be working with physicians at leading institutions as we begin making the test available to help ease what is often a challenging diagnostic journey for patients with IPF or other ILD. Our Early Access Program — while limited to a smaller number of institutions — will enable us to begin providing access to the test in advance of its anticipated, nationwide commercial expansion in 2019.”
The launch of Veracyte’s program follows a recent questionnaire conducted by the Pulmonary Fibrosis Foundation that found that many patients with IPF or other ILDs experience substantial delays in diagnosis, frequent misdiagnosis, invasive and costly diagnostic procedures, and considerable use of healthcare resources.
Based on observations from the survey, researchers suggested that better diagnostic tools and more education for physicians is needed to improve the diagnosis of patients with ILDs.
IPF diagnosis is usually done through high-resolution computed tomography imaging to identify usual interstitial pneumonia (UIP), a typical diagnostic pattern in IPF patients. However, this approach frequently provides inconclusive results, leading to the need for surgical procedures that enable a more definitive diagnosis.
Envisia Genomic Classifier combines two technologies to differentiate UIP from non-UIP: machine learning and RNA sequencing — a technique used to detect the presence of the nucleic acid RNA from specific species.
Patients’ samples are obtained through transbronchial biopsy, a common nonsurgical procedure to evaluate the lungs. Samples are then tested in the 190-gene test that detects UIP with high accuracy — 88 percent specificity and 70 percent sensitivity.
IPF is one of the most common ILDs, but it also considered one of the most difficult to diagnose.
“Obtaining an accurate, timely IPF diagnosis is important given the availability of new drugs that can slow the progression of this debilitating disease, as well as the need to avoid inappropriate and potentially harmful treatment,” said S. Samuel Weigt, MD, associate professor of medicine at UCLA and director of UCLA Health’s Interstitial Lung Disease Center.
“Unfortunately, IPF is often difficult to distinguish from other ILD [interstitial lung diseases], even when with the most advanced imaging technologies. Further, diagnostic surgery is risky, expensive and may not be viable for some patients. We are pleased to be one of the few medical facilities in the country to have access to this breakthrough technology,” he said.