Review article
A quantitative approach to neuropsychiatry: The why and the how

https://doi.org/10.1016/j.neubiorev.2017.12.008Get rights and content
Under a Creative Commons license
open access

Highlights

  • The PRISM project will provide a quantitative biological approach across neuropsychiatric diseases.

  • Quantifiable biological parameters for social withdrawal and cognitive deficits will be assessed.

  • Homologous preclinical and clinical paradigms will be implemented to deliver predictive animal models.

  • A molecular landscape with functional signalling pathways for social withdrawal will be built.

  • The PRISM project aims to provide solutions to the growing public health challenges of psychiatry and neurology.

Abstract

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 stagnated. The recently EU-funded PRISM 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. By combining clinical data sets from major worldwide disease cohorts and by applying innovative technologies to deeply phenotype stratified patient groups, we will define a set of quantifiable biological parameters for social withdrawal and cognitive deficits common to Schizophrenia (SZ), Major Depression (MD), and Alzheimer’s Disease (AD). These studies aim to provide new classification and assessment tools for social and cognitive performance across neuropsychiatric disorders, clinically relevant substrates for treatment development, and predictive, preclinical animal systems. With patients and regulatory agencies, we seek to provide clear routes for the future translation and regulatory approval for new treatments and provide solutions to the growing public health challenges of psychiatry and neurology.

Keywords

Schizophrenia
Alzheimer’s Disease
Major Depression
Behaviour
EEG
Neuro-imaging
Genetics
Smartphone technology
Mouse
Human
Cross-disorder
Transdiagnostic
Drug discovery
Translational research
Sensory processing
Social withdrawal
Attention
Working memory
Quantitative biology

Cited by (0)