AI-Guided Pharmacogenomics for Personalised Antidepressant Therapy

Loading...
Thumbnail Image
Authors
Kumar, Soorya Kanath Sudee
Issue Date
2025-11
Type
Other
Language
Keywords
Research Projects
Organizational Units
Journal Issue
Alternative Title
Abstract

This poster explores the transformative role of artificial intelligence (AI) in enhancing pharmacogenomic techniques to personalise antidepressant prescriptions, focusing on implementations and perceptions in India and Europe. Using a mixed-methods design combining quantitative surveys and qualitative interviews, the research assesses AI's potential to reduce trial-and-error prescribing, improve treatment accuracy, and address regional ethical, regulatory, and infrastructure challenges. Findings show strong agreement on AI's effectiveness in improving prescription accuracy and personalising therapy, with Europe demonstrating higher awareness and regulatory structure compared to India. Key barriers include data privacy concerns, training deficits, and ethical uncertainties. The study concludes that AI-driven pharmacogenomics can significantly optimize antidepressant therapy but requires targeted clinician training, robust ethical and data protection frameworks, and investment in genetic testing infrastructure. Cross-regional collaboration is essential to harmonize regulations and maximise AI benefits in personalised mental health care.

Description
Citation
Publisher
License
Journal
Volume
Issue
PubMed ID
DOI
ISSN
EISSN