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Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/111824
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dc.contributor.authorBousman, C.-
dc.contributor.authorForbes, M.-
dc.contributor.authorJayaram, M.-
dc.contributor.authorEyre, H.-
dc.contributor.authorReynolds, C.-
dc.contributor.authorBerk, M.-
dc.contributor.authorHopwood, M.-
dc.contributor.authorNg, C.-
dc.date.issued2017-
dc.identifier.citationBMC Psychiatry, 2017; 17(1):60-1-60-7-
dc.identifier.issn1471-244X-
dc.identifier.issn1471-244X-
dc.identifier.urihttp://hdl.handle.net/2440/111824-
dc.descriptionPublished online: 08 February 2017-
dc.description.abstractAbout half of people who take antidepressants do not respond and many experience adverse effects. These detrimental outcomes are in part a result of the impact of an individual's genetic profile on pharmacokinetics and pharmcodynamics. If known and made available to clinicians, this could improve decision-making and antidepressant therapy outcomes. This has spurred the development of numerous pharmacogenetic-based decision support tools. In this article, we provide an overview of pharmacogenetic decision support tools, with particular focus on tools relevant to antidepressants. We briefly describe the evolution and current state of antidepressant pharmacogenetic decision support tools in clinical practice, followed by the evidence-base for their use. Finally, we present a series of considerations for clinicians contemplating use of these tools and discuss the future of antidepressant pharmacogenetic decision support tools.-
dc.description.statementofresponsibilityChad A. Bousman, Malcolm Forbes, Mahesh Jayaram, Harris Eyre, Charles F. Reynolds, Michael Berk, Malcolm Hopwood and Chee Ng-
dc.language.isoen-
dc.publisherBioMed Central-
dc.rights© The Author(s). 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.-
dc.source.urihttp://dx.doi.org/10.1186/s12888-017-1230-5-
dc.subjectPrecision Medicine-
dc.subjectPharmacogenetics-
dc.subjectMajor depressive disorder-
dc.subjectPsychiatry-
dc.subjectDecision Support-
dc.titleAntidepressant prescribing in the precision medicine era: a prescriber's primer on pharmacogenetic tools-
dc.typeJournal article-
dc.identifier.doi10.1186/s12888-017-1230-5-
dc.relation.granthttp://purl.org/au-research/grants/nhmrc/1059660-
pubs.publication-statusPublished-
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Psychiatry publications

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