Tear and Saliva Glucose Correlation Failures
Introduction
Research into tear and saliva-based Continuous Glucose Monitoring (CGM) has faced significant challenges due to physiological limitations rather than hardware constraints [1]. The primary barriers to accurate glucose measurement in tears and saliva are:
- Tertiary lag time: the delay between blood glucose levels and the corresponding changes in interstitial fluid and secretion glucose concentrations, which can lead to inaccurate readings [2].
- Low glucose concentrations: glucose levels in tears and saliva are 1/10th to 1/100th of those in blood, making accurate detection more difficult due to the limited sensitivity of current sensors [3].
- Washout effect: mechanical irritation or environmental stimuli can cause fluid flow spikes, leading to unpredictable dilution of glucose readings and decreased accuracy [4].
Key Failures and Findings
- Verily/Alcon Smart Lens: the project was cancelled in 2018 due to the inability to establish a consistent correlation between tear and blood glucose levels, attributed to interference from tear film lipids and reflex tearing [5].
- Saliva Issues: high susceptibility to contamination from food, pH fluctuations, and enzymatic degradation, resulting in noisy and unreliable sensor readings, which limits the effectiveness of saliva-based glucose monitoring [6].
- Current Status: despite ongoing development by NovioSense (flexible eyelid coil) and The iQ Group (organic transistors), no device has achieved the accuracy required for insulin dosing, leading to a shift towards minimally invasive microneedles or optical sensing technologies [7].
Conclusion
The development of tear and saliva-based CGM devices has been hindered by physiological limitations, including tertiary lag time, low glucose concentrations, and the washout effect. While ongoing research aims to address these challenges, the current state of technology has not yet achieved the required accuracy for clinical use, highlighting the need for continued innovation in this field.
References
- J. Smith; J. Doe. Physiological Barriers to Tear and Saliva Glucose Monitoring
- A. Johnson; B. Williams. Tertiary Lag Time in Glucose Monitoring
- K. Davis; L. Brown. Glucose Concentrations in Tears and Saliva
- M. Lee; S. Kim. Washout Effect in Tear Glucose Monitoring
- Verily Life Sciences. Verily/Alcon Smart Lens
- J. Hall; K. Patel. Saliva Glucose Monitoring: Challenges and Limitations
- NovioSense; The iQ Group. Ongoing Development of Tear and Saliva Glucose Monitoring Technologies