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Isentio is granted NOK 2.6M to develop tools for diagnosis of fungal infections

Isentio AS has been awarded a grant of NOK 2.6M from Innovation Norway to develop a sequence based analysis tool for the diagnosis of fungal infections. ARUP Laboratories, Salt Lake City, Utah, USA will be a partner in this project.

Fungi can cause serious infections, particularly in immunocompromised patients. Good tools for fungal identification are lacking. This becomes an even bigger problem as an increasing number of fungi are causing infections and their clinical context is not well understood.

Isentio AS and ARUP Laboratories are heading up a joint project to create a fungal database that provides information important to identifying and reporting out clinical fungal samples, whether they be as isolates or as a mix with other fungi or bacteria.

“We are extremely happy to have ARUP Laboratories as a partner in the project. As one of the leading reference laboratories in the world, with thousands of samples being analyzed each day and a worldwide leader in innovative laboratory research and development, they are the perfect partner for such a project” says Camilla Huse Bondesson, CEO of Isentio.

DNA sequence based identification of fungal organisms has the potential to become a powerful tool for routine analysis of clinical samples. Particularly since mixed infections now can be identified with the RipSeq Mixed software from Isentio. Isentio will therefore continue to develop the RipSeq solution to enable identification of fungal infections by direct sequencing of clinical specimen.

NOTE: RipSeq is for research use only.

Emner

  • Data, datateknikk, programvare

Kategorier

  • fungal infections
  • soppinfeksjoner
  • diagnostic software
  • diagnostik
  • molecular diagnostics
  • ripseq
  • sekvensering

About Isentio AS (www.isentio.com)
Isentio offers unique, online software solutions to facilitate analysis, interpretation and management of DNA sequencing data. RipSeq sequence-based analysis reduces the time needed to identify infectious pathogens, in single or poly-microbial samples, by up to 90% and provides answers where other methods fail. Fast, precise pathogen identification supports selection of optimal antibiotic regimes with the potential to reduce health care costs.

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