Addressing the grand societal healthcare challenges, regarding both human suffering and the ever-growing cost of healthcare, necessitates a paradigm shift from generic and reactive medicine to personalized, proactive, and preventive medicine. Accordingly, wearable biomonitoring technologies play a critical role in promoting awareness and adoption of healthy lifestyles for disease prevention and enabling actionable feedback. Currently, commercialized wearable sensors and Internet of Things devices are only capable of tracking physical activities and vital signs, and fail to non-invasively access molecular-level biomarker information to provide insight into the body's dynamic chemistry. Also, at the current state, blood-based sensing techniques that provide direct measurements of circulating biomarkers cannot be scaled across the general population for point-of-person daily monitoring (due to their invasive nature and risk of infection). Alternatively, other biofluids can be probed, which share biomarker partitioning pathways with blood and can be accessed non-invasively. In this regard, sweat is an excellent candidate, because it is a rich source of biomarkers that originally diffused from blood and can be retrieved in a wearable format and without user intervention. By attaining reasonable level of predictive accuracy in providing non-invasive proxy measures of blood biomarkers, wearable sweat sensors allow for monitoring the well-being of individuals and enable actionable feedback to improve their health and performance.
The proposed research addresses fundamental bottlenecks critical to advancing the field of sweat-based biosensing at device, sensor, and data analytics levels. In the proposed approach, by devising programmable iontophoretic sweat induction and microfluidic interfaces, the interfering effects of confounders and contamination will be mitigated. A high throughput electro-modification sensor development methodology will be devised for the multiplexed construction of chemically diverse sensing features in microarray formats, which will be tailored to accurately measure sweat biomarkers on body. Furthermore, an analytical framework will be developed to provide undistorted measures of the sweat biomarkers, thus rendering individual-level temporal estimates of blood biomarker levels to establish the correlation and clinical utility of sweat readings. Upon achieving the proposed milestones, a new class of biomarker analysis platforms, with real-time information sensing and transmission capabilities, emerge that can facilitate general population well-being and performance monitoring. Equally important, the versatility of the devised methodologies allows for their use, with minimal reconfiguration, to target biomarkers in other biofluids (interstitial fluid, saliva, urine, and blood). The large data sets that will be collected through these technologies will expand our understanding of personal and societal health needs. Future generations of scientist will be trained by synergistically integrating the outreach and education plans with research activities. A diverse community of high school/undergraduate students will participate in research. The research findings will be integrated in the biosensing courses that the PI is developing.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
