Biocartis Receives €1.4M to Support Development of Rapid NGS Prep Panels
News Nov 01, 2016
The NGS Prep Panels that Biocartis has under development combine the company’s best-in-class sample preparation technologies for oncology applications (such as FFPE1 tissue, cytological materials or plasma) integrated in the Idylla™ cartridge, with the generation of DNA libraries2 that contain a wide range of enriched genomic information relevant for oncology diagnostics. Both steps comprise the majority of the NGS workflow. As such, the NGS Prep Panels can function as a gateway to NGS by providing standardization and automation of key sample and library preparatory steps. This is expected to reduce the total hands-on and turnaround time of a standard NGS workflow with 50%-75%3 and will significantly reduce workflow errors given, amongst others, the high level of automation.
While the Idylla™ qPCR4 technology is ideally suited for fast and cost-effective first-line detection of the most common pre-identified cancer driving gene alterations, NGS technology is capable of detecting a broader spectrum of gene alterations, which is particularly useful to detect less frequently occurring cancer-driving mutations. The NGS Prep Panels under development, from a health economic perspective, are as such a cost-efficient way to bridge these complementary technologies.
Nicolas Vergauwe, Head of Innovation at Biocartis, commented: “Once again, Biocartis is grateful for the financial support it has received from VLAIO. Thanks to this project, Biocartis can further expand the true platform capabilities of Idylla™ by the development of highly innovative NGS Prep Panels, complimentary to first-line rapid and highly accurate Idylla™ testing for the detection of the most common mutations. This will open doors to ensure that a larger population has access to the newest targeted cancer treatments via Idylla™ triaging, which is expected to improve treatment outcomes while lowering healthcare costs.”
Staphylococcus epidermidis is an ubiquitous colonizer of healthy human skin, but it is also a notorious source of serious nosocomial infections. Now, a new machine learning technique will help predict the risk of developing a serious, and possibly life-threatening S. epidermidis infection.READ MORE