Recording Physiological Data
The present invention is a method of detecting neurological disease in a patient, specifically epileptogenesis, very early-on – before first seizures develop. The method consists of the detection of abnormal physiological parameters by statistical assessment of correlations. In animal studies, signals can be identified weeks or longer before an animal’s first seizures that distinguish them from animals that don’t become epileptic. Non-epileptic animals had consistent, unvarying results from the onset of the analysis until time-of-death. This discovery can be utilized to identify potential patients at risk of developing epilepsy, track the progression of epileptogenesis, and predict the occurrence of subclinical epileptic activity and seizures. The researchers have shown that the high fidelity analysis is quite robust for a broad range of analysis parameters.
Application & Market Utility
There is currently no reliable, predictive biomarker of epileptogenesis. This innovation can introduce early and effective interventions to prevent establishment of epilepsy as well as evaluate therapeutic efficacy of such treatments. The technology can phenotype animals that will become epileptic and assess efficacy of potential interventions, and could act as a non-invasive biomarker to detect other high-risk patient populations: post traumatic brain injuries, post-infection, post-anoxic/ischemic, and post-surgical.
Seeking research collaboration and licensing opportunities. U.S. patent application 16/396,316 filed 4/26/2019.