Transforming the measurement of disease progression in vivo using noninvasive biosensors.
Glympse detects real-time biological changes at the site of the disease.
Glympse’s disruptive, noninvasive technology directly queries disease activity in the body. The platform can transform disease detection, identify treatment responders, monitor the course of disease, and track patients back to health.
We are focused on measuring disease trajectory by querying biological activity through our novel technology: activity-based sensors that are bioengineered and tunable to any protease-mediated disease.
Bioengineered, tunable sensors are designed for each disease state.
The biosensors localize to diseased tissue to measure the activity of proteases that are dysregulated in the disease.
Within an hour of administration, the biosensors are excreted in urine, detected using standard laboratory approaches, analyzed with a proprietary classifier unique to the disease state, and reported as clinically actionable results.
The results from each patient are amassed into a data engine that enhances the precision of the classifiers and powers future discovery.
Our cutting-edge technology is transforming the way diseases are understood. Learn about our noninvasive method to deliver real-time, clinically actionable disease results.
Our sensors are bioengineered to query the activity of proteases – a class of enzymes that drive critical disease pathways – to create accurate, sensitive, and specific markers. The biosensors are tailor-made and refined to each protease-mediated disease and are easily detected in a simple, noninvasive urine test. It’s the new frontier.
By measuring a unique aspect of biology that no other technology captures and combining these insights with other biological and clinical research, our data engine addresses a significant opportunity in the digital health era.
We are building a comprehensive database of real-time biological activity in the human body that drives insights to validate drug-target engagement, determine responders and non-responders, and drive earlier and improved outcomes for patients.
By utilizing machine learning to analyze rich data sets of signals detected from patients, we can provide a more complete map of human biology and disease activity.