Abstract

Precision psychiatry is an exciting new approach that is rapidly gaining traction. One key goal of precision psychiatry is to use detailed information from individual patients to select and tailor treatments. Although clinicians have always needed to apply their knowledge to treat the individual patient in front of them, the knowledge base they have relied on to do so has typically come from research on groups of patients, mostly groups based on diagnosis. However, with recent technological and computational advances (non-invasive neuroimaging techniques, modern genetic sequencing, machine learning algorithms, etc), a wealth of new types of information for precision psychiatry is now available. These advances have been paralleled by funding initiatives pushing researchers to more strongly consider individual differences rather than diagnostic groups (e.g., the National Institute of Mental Health’s Research Domain Criteria initiative [ [1] Insel T. Cuthbert B. Garvey M. Heinssen R. Pine D.S. Quinn K. et al. Research domain criteria (RDoC): toward a new classification framework for research on mental disorders. Am J Psychiatry. 2010; 167: 748-751https://doi.org/10.1176/appi.ajp.2010.09091379 Crossref PubMed Scopus (4102) Google Scholar ], the BRAIN initiative [ [2] The Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative. https://www.braininitiative.nih.gov/ [Accessed 12 March, 2019]. Google Scholar ]). In addition, large-scale genetic studies of psychiatric disorders have highlighted that these disorders are highly heterogeneous, further supporting the need for an individualized approach to treatment [ [3] Visscher P.M. Wray N.R. Zhang Q. Sklar P. McCarthy M.I. Brown M.A. et al. 10 years of GWAS discovery: biology, function, and translation. Am J Human Genetics. 2017; 101: 5-22 Abstract Full Text Full Text PDF PubMed Scopus (1618) Google Scholar ]. Taken together, there is now an enormous amount of potential information to be used for precision psychiatry.

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