Integrating clinical pharmacology and artificial intelligence: potential benefits, challenges, and role of clinical pharmacologists.

IF 3.6 3区 医学 Q2 PHARMACOLOGY & PHARMACY Expert Review of Clinical Pharmacology Pub Date : 2024-04-01 Epub Date: 2024-02-15 DOI:10.1080/17512433.2024.2317963
Harmanjit Singh, Dwividendra Kumar Nim, Aaronbir Singh Randhawa, Saher Ahluwalia
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Abstract

Introduction: The integration of artificial intelligence (AI) into clinical pharmacology could be a potential approach for accelerating drug discovery and development, improving patient care, and streamlining medical research processes.

Areas covered: We reviewed the current state of AI applications in clinical pharmacology, focusing on drug discovery and development, precision medicine, pharmacovigilance, and other ventures. Key AI applications in clinical pharmacology are examined, including machine learning, natural language processing, deep learning, and reinforcement learning etc. Additionally, the evolving role of clinical pharmacologists, ethical considerations, and challenges in implementing AI in clinical pharmacology are discussed.

Expert opinion: The AI could be instrumental in accelerating drug discovery, predicting drug safety and efficacy, and optimizing clinical trial designs. It can play a vital role in precision medicine by helping in personalized drug dosing, treatment selection, and predicting drug response based on genetic, clinical, and environmental factors. The role of AI in pharmacovigilance, such as signal detection and adverse event prediction, is also promising. The collaboration between clinical pharmacologists and AI experts also poses certain ethical and practical challenges. Clinical pharmacologists can be instrumental in shaping the future of AI-driven clinical pharmacology and contribute to the improvement of healthcare systems.

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整合临床药理学和人工智能:潜在的益处、挑战和临床药理学家的作用。
简介:将人工智能(AI)融入临床药理学是加速药物研发、改善患者护理和简化医学研究流程的潜在方法:将人工智能(AI)融入临床药理学可能是加速药物发现与开发、改善患者护理和简化医学研究流程的一种潜在方法:我们回顾了人工智能在临床药理学中的应用现状,重点关注药物发现与开发、精准医疗、药物警戒和其他风险投资。研究了人工智能在临床药理学中的主要应用,包括机器学习、自然语言处理、深度学习和强化学习等。此外,还讨论了临床药理学家不断演变的角色、伦理考虑以及在临床药理学中实施人工智能所面临的挑战:人工智能在加速药物发现、预测药物安全性和有效性以及优化临床试验设计方面可发挥重要作用。它可以在精准医疗中发挥重要作用,帮助进行个性化药物剂量、治疗选择,并根据遗传、临床和环境因素预测药物反应。人工智能在药物警戒(如信号检测和不良事件预测)方面也大有可为。临床药理学家和人工智能专家之间的合作也带来了一定的伦理和实践挑战。临床药理学家可以在塑造人工智能驱动的临床药理学未来方面发挥重要作用,并为改善医疗保健系统做出贡献。
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来源期刊
Expert Review of Clinical Pharmacology
Expert Review of Clinical Pharmacology PHARMACOLOGY & PHARMACY-
CiteScore
7.30
自引率
2.30%
发文量
127
期刊介绍: Advances in drug development technologies are yielding innovative new therapies, from potentially lifesaving medicines to lifestyle products. In recent years, however, the cost of developing new drugs has soared, and concerns over drug resistance and pharmacoeconomics have come to the fore. Adverse reactions experienced at the clinical trial level serve as a constant reminder of the importance of rigorous safety and toxicity testing. Furthermore the advent of pharmacogenomics and ‘individualized’ approaches to therapy will demand a fresh approach to drug evaluation and healthcare delivery. Clinical Pharmacology provides an essential role in integrating the expertise of all of the specialists and players who are active in meeting such challenges in modern biomedical practice.
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