AxoSim Technologies Wins Annual BioChallenge During Innovation Louisiana

The BioChallenge is a pitch competition that puts companies head to head for a chance to win $25,000. The New Orleans BioInnovation Center (NOBIC), organizers of the event, has announced the winner of the November 18th pitch competition that took place during Innovation Louisiana, a life sciences entrepreneurship conference in New Orleans:

AxoSim TechnologiesAxoSim Technologies, a contract research organization dedicated to improving pharmaceutical development, has won the top prize, taking home $25,000.

According to NOBIC, the company is developing an advanced “nerve-on-a-chip” technology that helps predict neurological safety and efficacy of potential new drugs early in the development pipeline. The prize money will help support the company’s continued research and technology commercialization efforts.

The other three finalists in the 3rd annual BioChallenge competition on November 18 were:

  1. Crescentium: Crescentium’s initial product, the GemView LM, is designed to provide critical care physicians with a safe, inexpensive method of performing surgical procedures like tracheostomies while eliminating complications inherent in current procedures. The GemView LM gives physicians the advantage of continuous visualization of the larynx, trachea or lungs without obstructing or removing the patient’s airway.
  1. ORA Estuaries: ORA Estuaries grows oyster reefs into living coastal protection infrastructure. The company has developed OysterBreak, which takes advantage of the oyster’s inherent nature of clustering to form a coastal protection structure. The oysters not only form a natural breakwater that helps prevent shoreline erosion, but also help filter the water and grow faster than the sea level rise due to climate change.
  1. Taxor Diagnostics: Taxor is developing a diagnostic test to help doctors and patients personalize breast cancer treatment decisions by predicting whether a certain chemotherapy will be successful for a patient’s specific type of cancer. By making this prediction, patients can be spared from ineffective chemotherapy regimens and their side effects and also save valuable treatment time.