Autism Spectrum Disorder (ASD) affects 1 in 59 children – that’s over 10 million in Europe and the US, with costs to society 5 times as high as stroke or hypertension. Current diagnosis of ASD relies on behavioral questionnaires and semi-structured interactive evaluations of ASD symptoms. This clinical assessment is fully dependent on the expertise of the clinician. Further, after diagnosis, there is currently no method of identifying patients for which certain therapies may work, and also no approved drugs or other treatments that actually
treat the core symptoms of ASD. All this because of poor insight into the underlying biological mechanisms of ASD.
There is a huge opportunity to provide accurate measurement of the underlying biological mechanisms of ASD and mental health issues in general. Shifting from an subjective, symptoms based endpoint towards an objective, physiological based endpoint will change the lives of people living with a mental health issue.
By combining EEG with Artificial Intelligence, NBT Autism is developing a method to objectively measure and monitor the physiological processes in the brain that are related to ASD. NBT Autism uses the latest theories in neuroscience with advanced machine learning techniques to analyse EEG signals. By analysing imbalances in the excitation and inhibition of neuronal firing, it is possible not only to objectively identify a disorder that until now was solely based on subjective observation of symptoms, but also predict the effectiveness of its treatment. Furthermore, this method could greatly contribute to drug discovery and drug repurposing.
The method has been validated in 263 patients. Patent application filed in Q1 2018. The machine learning algorithms are protected by copyrights.
Meet the team
Ruben Mikkers – NLC