Artificial intelligence for precision medicine

IF 2.1 4区医学 Q3 PHARMACOLOGY & PHARMACY

Therapie Pub Date : 2026-03-01 Epub Date: 2025-10-08 DOI:10.1016/j.therap.2025.10.003

Marie-Elise Martel , Adan José-Garcia , Celine Vens , Maarten De Vos , Vincent Sobanski

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引用次数: 0

Abstract

Introduction

Precision medicine aims to tailor healthcare decisions and interventions to the unique biological and clinical characteristics of each patient. The recent convergence of artificial intelligence (AI) with advances in digital health, omics, and big data analytics has accelerated progress toward this goal. AI technologies – particularly machine learning, deep learning, natural language processing and generative large language models – enable the rapid and meaningful analysis of complex biomedical datasets, supporting more individualized care.

Purpose of review

In this narrative review, we provide an accessible overview of the core principles of AI for healthcare professionals and explore its practical applications across the spectrum of precision medicine. Real-world examples highlight how AI is being used to enhance early diagnosis, guide treatment selection, support disease prevention, and even contribute directly to therapeutic interventions. Alongside these advances, we discuss critical limitations and challenges, including ethical considerations, algorithmic bias, data privacy concerns, environmental impact, and practical barriers to clinical implementation.

Conclusion

This review offers both an introduction to AI and a practical overview of how it is being used, and where its limitations lie, in precision medicine, with the goal of helping healthcare professionals understand these evolving tools and use them efficiently and responsibly in clinical practice.

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精准医疗的人工智能。

导读：精准医学旨在根据每位患者独特的生物学和临床特征量身定制医疗保健决策和干预措施。最近，人工智能（AI）与数字健康、组学和大数据分析的进步相结合，加速了实现这一目标的进程。人工智能技术，特别是机器学习、深度学习、自然语言处理和生成式大型语言模型，能够对复杂的生物医学数据集进行快速和有意义的分析，从而支持更加个性化的护理。综述目的：在这篇叙述性综述中，我们为医疗保健专业人员提供了人工智能核心原则的可访问概述，并探索其在整个精准医学领域的实际应用。现实世界的例子突出了人工智能如何用于加强早期诊断，指导治疗选择，支持疾病预防，甚至直接促进治疗干预。除了这些进步，我们还讨论了关键的限制和挑战，包括伦理考虑、算法偏见、数据隐私问题、环境影响和临床实施的实际障碍。结论：本综述既介绍了人工智能，也概述了人工智能在精准医学中的应用情况及其局限性，目的是帮助医疗保健专业人员了解这些不断发展的工具，并在临床实践中高效、负责任地使用它们。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Therapie 医学-药学

CiteScore

3.50

自引率

7.70%

发文量

132

审稿时长

57 days

期刊介绍： Thérapie is a peer-reviewed journal devoted to Clinical Pharmacology, Therapeutics, Pharmacokinetics, Pharmacovigilance, Addictovigilance, Social Pharmacology, Pharmacoepidemiology, Pharmacoeconomics and Evidence-Based-Medicine. Thérapie publishes in French or in English original articles, general reviews, letters to the editor reporting original findings, correspondence relating to articles or letters published in the Journal, short articles, editorials on up-to-date topics, Pharmacovigilance or Addictovigilance reports that follow the French "guidelines" concerning good practice in pharmacovigilance publications. The journal also publishes thematic issues on topical subject. The journal is indexed in the main international data bases and notably in: Biosis Previews/Biological Abstracts, Embase/Excerpta Medica, Medline/Index Medicus, Science Citation Index.