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Psychiatric Ratings using Intermediate Stratified Markers Sofia ref. 115916

The current nosology of neuropsychiatric disorders allows for a pragmatic approach to treatment choice, regulation and clinical research. However, without a biological rationale for these disorders, drug development has dramatical... see more

30/09/2019

RIJKSUNIVERSITEIT...

16M€

Project Budget: 16M€

Project leader

RIJKSUNIVERSITEIT GRONINGEN No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

PARTICIPATION DEPralty Sin fecha límite de participación.

Ver 24 Participantes

Financing granted El organismo H2020 notifico la concesión del proyecto The day 2019-09-30

IMI2-2015-03-03: Linking Clinical Neuropsychiatry an... Scope:Specific Challenge The challenge is to initiate the process to move towards a quantitative bio...

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characteristics of the participant

Este proyecto no cuenta con búsquedas de partenariado abiertas en este momento.

Private Information

No hay información privada compartida para este proyecto. Habla con el coordinador.

24 Participantes

RIJKSUNIVERSITEIT GRONINGEN

2.11M€ | Leader

BIOTRIAL

350.00K€ | participant

P1VITAL PRODUCTS LIMITED

460.42K€ | participant

CONCENTRIS RESEARCH MANAGEME...

315.00K€ | participant

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Project duration: 45 months Date Start: 2015-12-18
End date: 2019-09-30

Project leader

RIJKSUNIVERSITEIT GRONINGEN No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Project Budget 16M€

participation deadline Sin fecha límite de participación.

Project description The current nosology of neuropsychiatric disorders allows for a pragmatic approach to treatment choice, regulation and clinical research. However, without a biological rationale for these disorders, drug development has dramatically stagnated in the past decades. In a coordinated effort encompassing academic experts, SMEs, patient and family organizations, regulators, ECNP and EFPIA partners, this project aims to develop a quantitative biological approach to the understanding and classification of neuropsychiatric diseases to accelerate the discovery and development of better treatments for patients. This project will concentrate on Schizophrenia (SZ), Alzheimer’s disease (AD), and Major Depression (MD), as these disorders share part of their symptomatology, in particular social withdrawal and certain cognitive deficits, such as deficits in attention, working memory and sensory processing. By applying innovative technologies (e.g. EEG, cognitive tasks, (f)MRI, smartphone monitoring, and (epi-)genetics) to deep phenotype a clinical cohort of SZ and AD patients combined with a wider analysis of existing clinical data sets from major European and global disease cohorts that also include MD, we will define a set of quantifiable biological parameters best able to cluster and differentiate SZ, AD, and MD patients that do, or do not, exhibit social withdrawal. First, by mining large European SZ, AD and MD cohort datasets with already available social and cognitive proxy measures, and, second, by obtaining objective measures of social exploration levels (using a novel smartphone application), phenotypic relationships with social and cognitive measures will be further tested. For instance we might predict that socially withdrawn individuals may have lower cognitive functioning and poorer clinical course compared to those who are more socially engaged.

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