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Acurion raises $4.3M for oncology precision medicine platform

The company’s platform, OncoGaze, analyzes genomic biomarkers from routine clinical slides to help clinicians select personalized therapies.
By Jessica Hagen , Executive Editor
Scientist in a lab

Photo: andresr/Getty Images 

San Diego-based Acurion, which offers an AI-powered oncology precision medicine technology, announced it closed an oversubscribed $4.3 million seed financing round.

TK & Partners led the round, with participation from Mesa Verde Venture Partners, the National Foundation for Cancer Research, the Asian Fund for Cancer Research and Bootstrap Ventures, among other investors.  

WHAT IT DOES

Acurion's image analysis tool, OncoGaze, uses biomarkers to help oncologists provide personalized treatment options to patients. The company says OncoGaze can detect genomic biomarkers from routine clinical slides for every cancer, allowing for real-time therapy selection.

The company will use the funds to improve its platform, support clinical validation, prepare for regulatory clearance and for commercialization.  

"AI has the potential to reshape how we detect and act on cancer biomarkers," said Carey Ng, Ph.D., managing partner at Mesa Verde Venture Partners. "What stood out to us about Acurion is their ability to translate complex science into a solution that fits directly into existing clinical workflows. This is the kind of innovation that can expand access to precision oncology at scale."  

MARKET SNAPSHOT

Precision medicine is transforming cancer care, according to the American Cancer Society. Personalized medicine uses information about an individual's proteins, genes and other factors to guide clinical decisions pertaining to prevention, diagnosis and treatment.

Another company offering biomarker testing to predict treatment response is AI-enabled computational pathology company PathAI, which uses AI to analyze digitized tissue slides and extract diagnostic and biomarker insights. The technology can quantify tumor characteristics and help predict treatment response.