A quantitative approach to neuropsychiatry: The why and the how

Neurosci Biobehav Rev. 2019 Feb:97:3-9. doi: 10.1016/j.neubiorev.2017.12.008. Epub 2017 Dec 12.


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

Publication types

  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Animals
  • Brain / physiopathology
  • Computational Biology*
  • Disease Models, Animal
  • Drug Discovery
  • Humans
  • Mental Disorders / diagnosis*
  • Mental Disorders / drug therapy*
  • Mental Disorders / physiopathology
  • Models, Neurological
  • Neuropsychiatry / methods*
  • Research Design