Breathomix
Breathomix is a leader in eNose technology and breath analysis, creating non-invasive diagnostic solutions to advance early disease detection and precision medicine across fields such as cancer, inflammatory, and infectious diseases. Their BreathBase® Solution enables reliable, reproducible analysis of the full spectrum of volatile organic compounds (VOCs) in exhaled breath, driving high-quality research and diagnostics. From hospitals to home care, Breathomix is pioneering accessible breath diagnostics to transform patient care through innovative breath analysis technology.
Industries
Nr. of Employees
small (1-50)
Products
Cloud-connected electronic-nose device for exhaled-breath VOC profiling
A point-of-care device that directs exhaled air across a cross-reactive MOS sensor array, acquires raw sensor signals during a standardized breath manoeuvre and transmits data in real time to a cloud analytics platform for pattern analysis and reporting.
Cloud-connected electronic-nose device for exhaled-breath VOC profiling
A point-of-care device that directs exhaled air across a cross-reactive MOS sensor array, acquires raw sensor signals during a standardized breath manoeuvre and transmits data in real time to a cloud analytics platform for pattern analysis and reporting.
Services
Real-time ingestion, processing and storage of raw and processed sensor data; web-accessible dashboards and exportable files for independent analysis; cloud-calibration to harmonize devices and enable pooled model use.
Operational support for multicenter prospective and real-world studies, including standardized measurement protocols, data collection workflows, and statistical/modeling assistance for generating and externally validating diagnostic and phenotyping models.
Provision of calibrated, cloud-connected breath-sensor devices, deployment support for integration with routine respiratory diagnostics and clinical workflows, and user training to ensure measurement quality and traceability.
Real-time ingestion, processing and storage of raw and processed sensor data; web-accessible dashboards and exportable files for independent analysis; cloud-calibration to harmonize devices and enable pooled model use.
Operational support for multicenter prospective and real-world studies, including standardized measurement protocols, data collection workflows, and statistical/modeling assistance for generating and externally validating diagnostic and phenotyping models.
Provision of calibrated, cloud-connected breath-sensor devices, deployment support for integration with routine respiratory diagnostics and clinical workflows, and user training to ensure measurement quality and traceability.
Expertise Areas
- Exhaled-breath analysis (breathomics)
- Clinical study design and multicenter validation
- Longitudinal monitoring and frequent-sampling study methods
- Machine learning and pattern-recognition for composite biomarkers
Key Technologies
- Cross-reactive MOS sensor arrays for VOC profiling
- Cloud-based analytics platforms and IoT data ingestion
- Pattern-recognition algorithms and machine learning
- Multivariate statistical methods (LASSO, PLS-DA, PCA, logistic regression)
News & Updates
The scientific development of the ‘SpiroNose’, a technically and clinically validated electronic nose specifically designed for use in the doctor’s office, is the result of the combined efforts of the multidisciplinary team of researchers from the Amsterdam University Medical Centers (UMC), location AMC, under the continuous guidance of professor Peter Sterk.
A study evaluated the accuracy of exhaled breath analysis using eNose technology for detection of early lung cancer in patients with Chronic Obstructive Pulmonary Disease (COPD). The study showed that eNose could identify COPD patients in whom lung cancer subsequently manifested within 2 years after inclusion.
The scientific development of the ‘SpiroNose’, a technically and clinically validated electronic nose specifically designed for use in the doctor’s office, is the result of the combined efforts of the multidisciplinary team of researchers from the Amsterdam University Medical Centers (UMC), location AMC, under the continuous guidance of professor Peter Sterk.
A study evaluated the accuracy of exhaled breath analysis using eNose technology for detection of early lung cancer in patients with Chronic Obstructive Pulmonary Disease (COPD). The study showed that eNose could identify COPD patients in whom lung cancer subsequently manifested within 2 years after inclusion.