The Tough Tech problem we are solving
Most medical decisions, over 70 percent by some estimates, depend on lab data, yet a lab test only captures a single moment in a body that is constantly changing. Biochemical signals such as hormones, proteins, and metabolites fluctuate throughout the day, and an annual blood draw offers just one frame from a year-long picture. Continuous glucose monitors closed this gap for a single molecule nearly three decades ago, but every other biomarker, from hormones to peptides, still requires a clinic visit and days or weeks of waiting for results. AI systems can already reason about health data as well as or better than many clinicians, but they cannot sense what is happening inside a patient's body in real time. Without a way to read biochemistry continuously, even the most capable AI is working blind.
About our solution
Continuity, with roots at MIT, is building a body-computer interface that reads human biochemistry in real time and streams it to AI systems. The team, which has also built biosensors at Caltech, Google X, Medtronic, Biolinq, and Seer, reprogrammed nanopore technology, the method behind real-time genome sequencing, into a single universal mechanism that can read hormones, proteins, metabolites, and other biomarkers in parallel, rather than requiring a custom mechanism for each one. In-vitro data supports the approach so far, and the first human test was successful. The resulting platform is designed to close the loop between sensing and action: AI detects changes in a person's biochemistry and adjusts treatment, nutrition, or medication without a lab visit in between.