LabCorp’s Enlighten Health Launches Innovative Genomics Initiative
News Sep 08, 2014
Laboratory Corporation of America® Holdings (LabCorp®) has launched Enlighten Health Genomics, a new business that builds on the diagnostic potential of Next-Generation Sequencing (NGS) technology. Enlighten Health Genomics is part of LabCorp’s Enlighten HealthSM, an innovation engine for provider and patient-facing services and tools that enhance treatment decisions, lower healthcare costs and improve patient outcomes.
Enlighten Health Genomics combines LabCorp’s world-class infrastructure and capabilities with a team of accomplished geneticists to offer state-of-the-art diagnostic capabilities, NGS analysis and interpretation, and informed genetic counseling. “Enlighten Health Genomics is an important part of LabCorp’s strategy to capitalize on our unique assets, create new sources of revenue from our core capabilities and meaningfully differentiate us from competitors,” said David P. King, LabCorp’s Chairman and Chief Executive Officer. “The launch of this business is another tangible step in the development of Enlighten Health, our initiative to create innovative tools and capabilities to enhance patient care.”
Later this year, Enlighten Health Genomics will introduce ExomeReveal, a whole exome sequencing testing service. Increasing evidence suggests that early genetic diagnosis can improve clinical outcomes, and ExomeReveal will provide genome-wide interpretation for children with serious childhood genetic diseases as well as additional diagnostic information for patients of any age.
“We believe that patients with serious genetic conditions require a thorough interpretation of their genome,” said Duke University genetics professor David Goldstein, who will chair Enlighten Health Genomics’ Scientific Advisory Board. “Our goal is to offer innovative and affordable diagnostic solutions to broad patient populations, making genomics a routine part of clinical decisions.”
Computer scientists at Carnegie Mellon University say neural networks and supervised machine learning techniques can efficiently characterize cells that have been studied using single cell RNA-sequencing (scRNA-seq). This finding could help researchers identify new cell subtypes and differentiate between healthy and diseased cells.