Molecules such as glucose, proteins, and other compounds can be ideal markers for detecting diseases such as diabetes due to their inherent biophotonic characteristics. However, the nature of the source of the sample (e.g., blood, urine, saliva) can introduce interference since some sample components can have similar photochemical properties when exposed to light with the same wavelength. Hence, the accuracy of results may not be consistent and reliable. Saliva should have fewer interfering proteins than blood-plasma samples with respect to biophotonic fluorescence. Thus, in these experiments, we have used saliva samples from 23 patients of different gender and age. Each saliva sample was mixed with a specific sensor constructed from DNA useful for fluorescence detection of glucose levels. The intensity of the fluorescence of each sample was compared to results from conventional clinical glycemic testing. The DNA sensor was developed based on synthetic biology, using a combination of synthetic and natural genetic parts: SNF3 + CYC1 Terminator + GAL1 Promoter + OGT + CYC1 Terminator + GAL1 Promoter + OGlcNA + CYC1 Terminator + GAL1 Promoter + EGFP. One of the advantages of this sensor is believed to be due to the presence of a specific gene related to a glycoprotein and/or protein modified with glucose found in high concentrations in saliva. The quantification of fluorescence measured using a photonics device showed greater sensitivity within a much shorter timeframe than the conventional glycemic techniques. Statistical analysis was carried out to enable specific identification, categorization, and quantification of the influence of different factors such as sample type (i.e. saliva), age, and gender of patient. Patients were grouped in different categories by integrating the different variables and were diagnosed with diabetes, pre-diabetes, or normal health based on predictions using the photonic data. Our investigation shows the advantage of using a non-invasive method such as a saliva test as well as a new highly sensitive detection method due to the interaction between the DNA-based sensor and the pho-tonicity.