Scope:Specific Challenge
CNS disorders are highly prevalent, chronic, and disabling diseases, with depression alone affecting an estimated 121 million people worldwide.
The onset of relapses in CNS disease causes changes in parameters related to sleep, physical activity, speech, cognition, social connectivity, memory that can be measured remotely and passively via unobtrusive on-body biosensors.
The vision of RADAR-CNS is to reduce cost and trauma to the patient and care-givers and reducing hospitalisations by predicting, and pre-empting relapses and reoccurrences via the use of remote assessment technologies.
Scope
This topic is planned to be focused on the three diseases of unipolar depression, multiple sclerosis and epilepsy. For each disease it is proposed that a non-interventional/observational study of subjects is undertaken with three objectives:
Characterisation of changes in disease state
Characterisation of changes in disease state due to drug effects
Prediction change in disease state from remote sensing data
Expected Impact <...
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Scope:Specific Challenge
CNS disorders are highly prevalent, chronic, and disabling diseases, with depression alone affecting an estimated 121 million people worldwide.
The onset of relapses in CNS disease causes changes in parameters related to sleep, physical activity, speech, cognition, social connectivity, memory that can be measured remotely and passively via unobtrusive on-body biosensors.
The vision of RADAR-CNS is to reduce cost and trauma to the patient and care-givers and reducing hospitalisations by predicting, and pre-empting relapses and reoccurrences via the use of remote assessment technologies.
Scope
This topic is planned to be focused on the three diseases of unipolar depression, multiple sclerosis and epilepsy. For each disease it is proposed that a non-interventional/observational study of subjects is undertaken with three objectives:
Characterisation of changes in disease state
Characterisation of changes in disease state due to drug effects
Prediction change in disease state from remote sensing data
Expected Impact
Identification and validation of biosignatures that predict relapse and track disease state changes in MS, Depression and Epilepsy.
Development of technology, data privacy controls and regulatory pathways necessary for approval of remote sensing solutions in real-world patients
Validation through clinical studies allowing these technologies to be rapidly brought to the patient.
Budget
IMI contribution: EUR 11 000 000
EFPIA contribution: EUR 11 000 000
Total: EUR 22 000 000
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