Breathe BioMedical has launched a groundbreaking multi-center observational study to evaluate its innovative breath test technology for early breast cancer detection. The trial, which commenced at the George Washington University Breast Center, focuses specifically on women with dense breast tissue, where traditional mammography faces significant limitations.
The study brings together leading experts in oncology, with Mayo Clinic's Dr. James Jakub, Surgical Oncologist and Professor of Surgery, and Dr. Pooja Advani, Breast Medical Oncologist and Researcher, serving as Co-Principal Investigators. Dr. David Barreto from George Washington School of Medicine and Health Sciences joins as Site Investigator.
Critical Need in Dense Breast Screening
The trial addresses a crucial gap in breast cancer screening capabilities. Currently, about 35 million women in the United States - representing 50% of the screening-eligible population - have dense breast tissue, putting them at 4-5 times higher risk of developing breast cancer compared to those without dense tissue. Standard mammography shows reduced effectiveness in these cases, with sensitivity rates dropping dramatically to as low as 40% in extremely dense breast tissue.
"Mammography alone is insufficient in detecting breast cancer for women with dense breast tissue, creating the need for accurate, and cost-effective adjunctive detection tools," explains Bill Dawes, CEO of Breathe BioMedical.
Advanced Breath Analysis Technology
The company's proprietary technology employs a sophisticated breath sampling system that captures alveolar breath samples using industry-standard sorbent tubes. These samples undergo analysis at a central laboratory using a specialized spectrometer capable of detecting compounds at parts per trillion levels.
The analytical process incorporates advanced Machine Learning Algorithms (MLA) to identify specific biomarkers and patterns associated with breast cancer. This data-driven approach aims to create a reliable, non-invasive diagnostic tool that could complement existing screening methods.
Expanding Research Collaboration
The study represents a significant step in validating breath-based cancer detection technology. "This data collection initiative will expand our existing data inventory, allowing us to evaluate our machine learning models across a broader and more diverse population," notes Dawes. The collaboration with prestigious institutions like Mayo Clinic and George Washington University sets the stage for potential expansion to additional clinical partners.
The research team will focus on comparing breath profiles between women with and without breast cancer, all having dense breast tissue. This comparative analysis aims to identify distinct patterns that could serve as reliable indicators of breast cancer presence, potentially offering a new pathway for early detection in this high-risk population.
