Unmet Need

The burden of central nervous system conditions costs the US healthcare system upwards of $800B annually, $28B for multiple sclerosis (MS). Specifically, delayed MS diagnoses and unpredictable disease progression create poor patient outcomes and inefficiencies across the healthcare system. There are a lack of objective, cost-effective, and non-invasive tools capable of monitoring disease progression.

Our Solution

The C. Light machine learning algorithms and instrument could efficiently, objectively, and non-invasively aid in the prognosis and monitoring of multiple sclerosis (MS) by measuring neurological activity through imaging the retina, which is also the front of the brain. It extracts eye motion at the cellular level - 150x more accurately than any pupil-tracking device on the market. Eye motion is then summarized within a TSLO readout report, providing actionable information to the patient care team. 

Through our novel eye motion data, C. Light will provide value throughout the care chain of MS: better outcomes and peace-of-mind for patients, treatment feedback and revenue for physicians, reduced overall healthcare costs for payers, and fast, objective outcomes measurements for therapeutic developers. Future applications of the core technology can extend to Alzheimer’s, Parkinson’s, ALS, and concussions.