Table 2.
Digital biomarker characteristics, challenges and sensing principles of molecular digital biomarkers in non-invasive biofluidsa.
| Sensing modality | Digital biomarker characteristics (current state of the art) | Technical challengesb | Main sensing principle | (Potential) molecular markersc | |||
|---|---|---|---|---|---|---|---|
| Non-invasive | Real-time | Continuous | Wearable | ||||
| Sweat | Yes, although some cases involve invasive stimulation of sweat production by iontophoresis | Yes | Yes, days to weeks | Yes, platforms include wristbands, tattoos, patches and textiles | - Low samples volumes - Low biomarker concentrations - Contamination of consecutive sweat samples - Artifacts from sweat rate, temperature, pH - Biomolecule distribution from blood to sweat (including time-lag) |
Selector-transducer (electrochemical, optical) | Metabolites (e.g., glucose, lactate, ethanol), electrolytes (e.g., pH, Na+, Cl−), heavy metals |
| Interstitial fluid | Currently minimally invasive due to subcutaneous insertion of cannula or interstitial fluid (ISF) collection by reverse iontophoresis | Yes | Yes, days to weeks | Yes, platforms include patches and wristbands | - Interference from sweating (with reverse iontophoresis) - Low sample volumes - Skin irritation due to ISF extraction - Biomolecule distribution from blood to interstitial fluid (including time-lag) |
Selector-transducer (electrochemical, optical) | Metabolites (e.g., glucose, urea, pharmaceuticals) |
| Tears | Yes | Yes | Yes, days to weeks | Yes, platform used is a contact lens | - Transparency - Biocompatibility - Application in humans - Biomolecule distribution from blood to tears (including time-lag) |
Selector-transducer (electrochemical, optical) | Metabolites (e.g., glucose, lactate) |
| Saliva | Yes | Yes | Yes, days to weeks | Yes, platforms include tooth enamel, mouthguard and pacifier | - Contamination with food residues, bacteria, etc. - Mechanical stress on sensor from mouth movements - Biocompatibility and user comfort - Biomolecule distribution from blood to saliva (including time-lag) |
Selector-transducer (electrochemical, optical) | Metabolites (e.g., cortisol, glucose, lactate, uric acid) |
| Breath | Yes | Yes | Currently limited, due to non-wearable platforms | No, mostly portable, although a wristband has been developed requiring active breathing onto the sensor | - No current wearable applications - Contamination from ambient air - Artifacts from airflow, humidity, ingested materials and temperature |
Selector-transducer (electrochemical, optical), spectroscopy | Metabolites (e.g., hydrogen, methane, sulfate) |
| Transcutaneous (tissue, blood) | Yes | Yes | Yes, months to years | Yes, depending on the spectroscopic method. | - Motion artifacts - Signal-to-noise - Need for frequent calibration - Often indirect measurement, which is sensitive to confounders |
Spectroscopy | Metabolites (e.g., oxygen saturation, fat, water, NADH, FAD, bilirubin), proteins (e.g., advanced glycated end products) |
This table is a compilation of information from multiple sources. Worthwhile reviews on the sensor technologies, molecular markers, and the related challenges can be found in (9, 10, 91).
Not including the general challenges of bio-sensing (e.g., stability, sensitivity, etc.), energy supply, wireless communication, material size and rigidity, and data analytics and security (91).
The list of potential biomarkers is broader if purely local biomolecules (e.g., proteins, peptides, bacteria) are also considered. The examples in this table are limited to those with potential to distribute from the systemic circulation to the biofluid of interest.