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Article

Pharmacogenomics-Driven Prediction of Antidepressant Treatment Outcomes: A Machine-Learning Approach With Multi-trial Replication.

Clinical pharmacology and therapeutics - 1 Oct 2019

Athreya Arjun P, Neavin Drew, Carrillo-Roa Tania, Skime Michelle, Biernacka Joanna, Frye Mark A, Rush A John, Wang Liewei, Binder Elisabeth B, Iyer Ravishankar K, Weinshilboum Richard M, Bobo William V

Abstract excerpt

We set out to determine whether machine learning-based algorithms that included functionally validated pharmacogenomic biomarkers joined with clinical measures could predict selective serotonin reuptake inhibitor (SSRI) remission/response in patients with major depressive disorder (MDD). We studied 1,030 white outpatients with MDD treated with citalopram/escitalopram in the Mayo Clinic Pharmacogenomics Research...

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Source

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Identifiers

PMID: 31012492
DOI: 10.1002/cpt.1482
PMCID: PMC6739122

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AHR
DEFB1
ERICH3
TSPAN5

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

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