AI-Driven Applications in Clinical Pharmacology and Translational Science: Insights From the ASCPT 2024 AI Preconference

IF 3.1 3区 医学 Q2 MEDICINE, RESEARCH & EXPERIMENTAL
Mohamed H. Shahin, Prashant Desai, Nadia Terranova, Yuanfang Guan, Tomáš Helikar, Sebastian Lobentanzer, Qi Liu, James Lu, Subha Madhavan, Gary Mo, Flora T. Musuamba, Jagdeep T. Podichetty, Jie Shen, Lei Xie, Mathew Wiens, Cynthia J. Musante
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Abstract

Artificial intelligence (AI) is driving innovation in clinical pharmacology and translational science with tools to advance drug development, clinical trials, and patient care. This review summarizes the key takeaways from the AI preconference at the American Society for Clinical Pharmacology and Therapeutics (ASCPT) 2024 Annual Meeting in Colorado Springs, where experts from academia, industry, and regulatory bodies discussed how AI is streamlining drug discovery, dosing strategies, outcome assessment, and patient care. The theme of the preconference was centered around how AI can empower clinical pharmacologists and translational researchers to make informed decisions and translate research findings into practice. The preconference also looked at the impact of large language models in biomedical research and how these tools are democratizing data analysis and empowering researchers. The application of explainable AI in predicting drug efficacy and safety, and the ethical considerations that should be applied when integrating AI into clinical and biomedical research were also touched upon. By sharing these diverse perspectives and real-world examples, this review shows how AI can be used in clinical pharmacology and translational science to bring efficiency and accelerate drug discovery and development to address patients' unmet clinical needs.

Abstract Image

人工智能在临床药理学和转化科学中的应用:来自ASCPT 2024人工智能预会议的见解
人工智能(AI)正在推动临床药理学和转化科学的创新,其工具可以推进药物开发、临床试验和患者护理。本综述总结了在科罗拉多斯普林斯举行的美国临床药理学与治疗学会(ASCPT) 2024年年会的人工智能会前会议的主要内容,来自学术界、工业界和监管机构的专家讨论了人工智能如何简化药物发现、给药策略、结果评估和患者护理。会前会议的主题集中在人工智能如何使临床药理学家和转化研究人员能够做出明智的决定并将研究成果转化为实践。会议前还讨论了大型语言模型在生物医学研究中的影响,以及这些工具如何使数据分析民主化并赋予研究人员权力。讨论了可解释人工智能在预测药物疗效和安全性方面的应用,以及将人工智能纳入临床和生物医学研究时应考虑的伦理问题。通过分享这些不同的观点和现实世界的例子,本综述展示了人工智能如何应用于临床药理学和转化科学,以提高效率并加速药物发现和开发,以解决患者未满足的临床需求。
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来源期刊
Cts-Clinical and Translational Science
Cts-Clinical and Translational Science 医学-医学:研究与实验
CiteScore
6.70
自引率
2.60%
发文量
234
审稿时长
6-12 weeks
期刊介绍: Clinical and Translational Science (CTS), an official journal of the American Society for Clinical Pharmacology and Therapeutics, highlights original translational medicine research that helps bridge laboratory discoveries with the diagnosis and treatment of human disease. Translational medicine is a multi-faceted discipline with a focus on translational therapeutics. In a broad sense, translational medicine bridges across the discovery, development, regulation, and utilization spectrum. Research may appear as Full Articles, Brief Reports, Commentaries, Phase Forwards (clinical trials), Reviews, or Tutorials. CTS also includes invited didactic content that covers the connections between clinical pharmacology and translational medicine. Best-in-class methodologies and best practices are also welcomed as Tutorials. These additional features provide context for research articles and facilitate understanding for a wide array of individuals interested in clinical and translational science. CTS welcomes high quality, scientifically sound, original manuscripts focused on clinical pharmacology and translational science, including animal, in vitro, in silico, and clinical studies supporting the breadth of drug discovery, development, regulation and clinical use of both traditional drugs and innovative modalities.
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