bioAffinity Technologies, Inc. announced publication of “Detection of early-stage lung cancer in sputum using automated flow cytometry and machine learning” detailing results of the Company's clinical trial for its non-invasive diagnostic CyPath Lung in Respiratory Research, one of the leading peer-reviewed open access journals in the field of respiratory medicine. CyPath Lung showed 92% sensitivity and 87% specificity in high-risk patients who had nodules smaller than 20 millimeters or no nodules in the lung, with an area under the ROC curve of 94%. Overall, the test resulted in specificity of 88% and sensitivity of 82%, similar to far more invasive procedures currently used to diagnose lung cancer.

More than half of those in the cancer cohort had early Stage I or II lung cancer. CyPath Lung detected multiple forms of cancer including adenocarcinoma, squamous cell carcinoma and small cell lung cancer. CyPath Lung uses flow cytometry, a method able to interrogate individual cells in a fraction of a second, and automated analysis to identify parameters in sputum that are indicative of cancer.

Unlike genomic or other molecular markers used in liquid biopsies, bioAffinity's CyPath® technology does not collect genetic material for evaluation. Instead, CyPath Lung analyzes the lung micro-environment and identifies whole cell populations that indicate cancer is present in the lung.