AI-Driven Pharmacogenomics and Precision Medicine: Future of Personalized Therapy

Year : 2026 | Volume : 03 | Issue : 02 | Page : 1 12
    By

    Kabhi Khanna,

  • Chetna Chhabra,

  • Rohit Saroha,

  • Karan Singh Gehlot,

  • Gauri Mudgal,

  1. Student, Department of Pharmacy, Adesh University, Bathinda, Punjab, India
  2. MD Resident, Department of Medicine, Santosh Deemed to be University, Ghaziabad, Uttar Pradesh, India
  3. Assistant Professor, Department of Physiology, Venkateshwara Institute of Medical Sciences, Gajraula, Amroha, Uttar Pradesh, India
  4. Senior Resident, Department of Orthopaedics, ESIC Medical College and Hospital, Faridabad, Haryana, India
  5. PhD Scholar and Assistant Professor, Department of Physiology, Divya Jyoti College of Dental Sciences and Research, Modinagar, Uttar Pradesh, India

Abstract

Pharmacogenomics and artificial intelligence (AI) are emerging as important drivers of precision medicine, enabling healthcare systems to adopt individualized therapeutic approaches. Pharmacogenomics examines how genetic variations influence drug response, efficacy, metabolism, and toxicity, while AI provides advanced computational tools for analyzing complex genomic and clinical data. This review highlights the integration of AI-driven pharmacogenomics in personalized therapy and its potential to improve treatment outcomes. Machine learning, deep learning, natural language processing, and big data analytics are increasingly used to identify genetic variants, predict drug responses, optimize medication selection and dosage, and reduce adverse drug reactions. These technologies support the interpretation of large-scale genomic information and facilitate evidence-based clinical decision-making. Significant applications have been demonstrated in oncology, cardiovascular diseases, neurological and psychiatric disorders, and rare genetic diseases, where personalized treatments can enhance therapeutic efficacy and patient safety. Recent advances in genomic sequencing, multi-omics integration, digital health technologies, explainable AI, and real-time patient monitoring have further expanded the scope of precision medicine. However, challenges related to data privacy, algorithm bias, regulatory frameworks, and clinical implementation remain. Future developments in explainable AI, predictive analytics, and AI-powered personalized therapy are expected to improve treatment precision and accelerate the realization of truly individualized healthcare. Overall, the convergence of AI and pharmacogenomics represents a transformative approach to modern medicine with substantial potential to improve patient outcomes and optimize therapeutic interventions.

Keywords: Artificial intelligence, pharmacogenomics, precision medicine, personalized therapy, machine learning

[This article belongs to Emerging Trends in Personalized Medicines ]

How to cite this article:
Kabhi Khanna, Chetna Chhabra, Rohit Saroha, Karan Singh Gehlot, Gauri Mudgal. AI-Driven Pharmacogenomics and Precision Medicine: Future of Personalized Therapy. Emerging Trends in Personalized Medicines. 2026; 03(02):1-12.
How to cite this URL:
Kabhi Khanna, Chetna Chhabra, Rohit Saroha, Karan Singh Gehlot, Gauri Mudgal. AI-Driven Pharmacogenomics and Precision Medicine: Future of Personalized Therapy. Emerging Trends in Personalized Medicines. 2026; 03(02):1-12. Available from: https://journals.stmjournals.com/etpm/article=2026/view=247547


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Regular Issue Subscription Review Article
Volume 03
Issue 02
Received 04/06/2026
Accepted 08/06/2026
Published 25/06/2026
Publication Time 21 Days
58

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