SepSense

During the Cornell Health Tech Hackathon 2023, my team and I developed a device for early detection of sepsis, winning First Place in Research-based Evidence.

Our early detection device had three main components: the biomarkers, transcutaneous electrodes, and display. Four biomarkers were chosen that were highly predictive of sepsis: resistin, IL-6, pancreatic stone protein, and brain natriuretic protein. Used in tandem, there is a high potential for extremely accurate early detection of sepsis.

The transcutaneous electrodes utilized needles with microwells. In these microwells, antibodies for the four aforementioned biomarkers are seeded, which will produce a change in impedance upon interaction with the intended protein.

Finally, these readings are projected to a display that physicians can utilize to interpret the continuous physical state of their patients. Machine learning models can also interpret the device readings to determine the risk of sepsis development and alert physicians accordingly.

I also leveraged healthcare management experience to provide a market & competitor analysis, estimate costs of development and manufacturing, and pitch financial viability of this project.