Traumatic brain injury biomarker company raises $6M for diagnostic

Banyan Biomarkers has rounded up $6 million in an initial round of venture funds to help back its work developing a new test for traumatic brain injury. The diagnostics company, however, didn't say who provided the cash, citing only unidentified private investors.

Banyan has been relying on a $26.3 million contract with the Department of Defense for much of its work, which zeroes in on two protein biomarkers licensed from the McKnight Brain Institute at the University of Florida. The proteins flood the system after a traumatic brain injury, making it theoretically possible to identify anyone who may be in need of special care.

Investigators recently discussed some data they had gathered on S100B plus apolipoprotein A1, saying that an effective test could ease the demand for CT scans in the emergency department, a major bottleneck at some institutions.

"We are extremely pleased to have such a group of highly experienced investors who will help us grow the company to the next level," said Jackson Streeter, CEO of Banyan Biomarkers. "Our groundbreaking research is poised to bring the first ever diagnostic blood test for TBI to the patient. This test will provide critical objective information to assist the clinician to properly triage and diagnose TBI."

The recent spate of high-profile sports cases involving traumatic brain injuries has helped highlight the prevalence of these instances. In its release Banyan said that about 1.4 million cases are tended to each year in the country's emergency departments, spurring more than $76 billion in costs.

- here's the press release
- get the story from MedPage Today

Suggested Articles

BD will begin working with Babson Diagnostics to help bring its lab-quality device for collecting blood from capillaries into retail pharmacies.

The former CEO of the molecular testing company Foundation Medicine, Troy Cox, has been named chairman of the Swiss big data firm Sophia Genetics.

Researchers at MIT used a machine-learning algorithm to uncover the potent antibiotic properties hiding within an old small-molecule candidate.