SYRACUSE, N.Y. — BiRed Imaging Inc. on Wednesday night was selected as the winner of the $10,000 Alan W. Rothschild Innovation Award at the Biotech Innovation Pitch.
BiRed Imaging Inc. is an Upstate Medical University startup developing an AI (artificial intelligence)-powered contactless breast-cancer screening technology, Upstate Medical said in its announcement.
A panel of six judges selected BiRed Imaging after listening to brief pitches from the seven competitors at the pitch competition held at the CNY Biotech Accelerator.
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One $5,000 runner-up prize went to sxRNA Technologies, which is developing an RNA “nanoswitch” that activates treatments only in targeted cells — offering new hope for diseases such as cancer and Alzheimer’s. Another $5,000 runner-up prize was awarded to Ergami Endoscopy, which is creating a low-cost robotic colonoscope insertion system designed to improve procedural efficiency, reduce patient pain and the need for sedation, and minimize endoscopy-related injuries among clinicians.
The finalists are all clients of the CNY Biotech Accelerator.
The Alan W. Rothschild Innovation Award at the Upstate Foundation honors Rothschild’s life, “which was one of creativity and entrepreneurial spirit and provides support to individuals and startups who demonstrate excellence in innovation,” Upstate Medical said. Its purpose is to “further the development and advancement of emerging science and new technologies.”
The Rothschild Award is the most recent success for BiRed Imaging. Earlier this year, it was awarded a $305,000 phase 1 grant from the National Science Foundation, Upstate Medical said.
About BiRed’s system
BiRed’s system uses AI and thermal imaging to detect tumors without breast compression or radiation. The BiRed imaging system detects the altered temperatures on the surface of a breast due to the increased metabolic activity of a cancerous tumor. It uses multispectral imaging that does not employ harmful radiation and is independent of breast density, which is a major concern in mammography. It uses well-established inverse heat transfer analysis to detect the tumor and predict its size and location within the breast. In preliminary clinical studies, this approach was used to study 24 biopsy-proven cancer patients with accurate predictions of tumor size and location.
