📄 Abstract
This review aims to explore the role of pharmacogenomics in predicting and optimizing antidepressant treatment outcomes in patients with Major Depressive Disorder (MDD). A narrative review was conducted, synthesizing findings from clinical trials, genetic studies, and pharmacogenomic platforms. The focus was on genetic polymorphisms influencing antidepressant metabolism (CYP2D6, CYP2C19) and response (SLC6A4, HTR2A, BDNF). Key clinical trials and current commercial pharmacogenomic tools were analyzed to assess efficacy, utility, and limitations. Studies demonstrate that pharmacogenomic-guided therapy can enhance treatment response and reduce adverse effects compared to standard care. Specific genetic variants significantly affect drug metabolism and therapeutic outcomes, suggesting utility in guiding antidepressant selection. However, challenges such as limited predictive power, high costs, and population-specific variability remain barriers to widespread implementation. Pharmacogenomics offers a promising path toward personalized psychiatry by minimizing trial- and-error prescribing. Future integration of multi-omics data and AI-driven tools may further improve its clinical relevance and accessibility.
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📚 How to Cite:
Abhiraj B. Amolik, Vishal S. Gaikwad, Abhijeet R. Rode , PHARMACOGENOMICS OF ANTIDEPRESSANT THERAPY: IDENTIFYING GENETIC PREDICTORS OF TREATMENT RESPONSE IN DEPRESSION- A REVIEW , Volume 11 , Issue 5, may 2025, EPRA International Journal of Multidisciplinary Research (IJMR) ,