张微微, 唐婧, 冀召帅, 胡永芳, 聂广孟, 张翀. 人工智能在临床药学中的应用进展J. 药学学报, 2025, 60(10): 3045-3059. DOI: 10.16438/j.0513-4870.2025-0565
引用本文: 张微微, 唐婧, 冀召帅, 胡永芳, 聂广孟, 张翀. 人工智能在临床药学中的应用进展J. 药学学报, 2025, 60(10): 3045-3059. DOI: 10.16438/j.0513-4870.2025-0565
ZHANG Wei-wei, TANG Jing, JI Zhao-shuai, HU Yong-fang, NIE Guang-meng, ZHANG Chong. Advances in the application of artificial intelligence in clinical pharmacyJ. Acta Pharmaceutica Sinica, 2025, 60(10): 3045-3059. DOI: 10.16438/j.0513-4870.2025-0565
Citation: ZHANG Wei-wei, TANG Jing, JI Zhao-shuai, HU Yong-fang, NIE Guang-meng, ZHANG Chong. Advances in the application of artificial intelligence in clinical pharmacyJ. Acta Pharmaceutica Sinica, 2025, 60(10): 3045-3059. DOI: 10.16438/j.0513-4870.2025-0565

人工智能在临床药学中的应用进展

Advances in the application of artificial intelligence in clinical pharmacy

  • 摘要: 人工智能(artificial intelligence, AI) 已经逐渐融入各个领域中并发挥重要作用。随着我国老龄化时代的到来和人民群众对健康需求的增加, AI在临床药学领域的应用备受关注。临床药学通过优化药物治疗、避免用药错误对保证临床用药安全、有效非常重要。AI由于具有强大的数据处理及分析能力、基于模型的强大预测能力等优势, 在临床药学领域具有广阔应用前景。本文介绍了目前AI在临床药学领域的应用进展, 聚焦于其在提升药物有效性方面及安全性方面的应用, 包括辅助药物选择、给药剂量及给药时间优化、智能化药学服务、药物相互作用预测、药物警戒、避免用药错误, 在梳理目前应用进展的基础上同时针对其在应用中存在的挑战展开讨论, 并提出可能的解决策略, 以期为后续研究及相关从业者提供参考。

     

    Abstract: Artificial intelligence (AI) has progressively integrated into various fields and plays a significant role. With the advent of China's aging population era and the growing public demand for healthcare, the application of AI in the field of clinical pharmacy has garnered considerable attention. Clinical pharmacy is crucial for ensuring the safety and effectiveness of clinical medication use by optimizing drug therapy and preventing medication errors. Due to its advantages, such as powerful data processing and analysis capabilities, and robust model-based predictive abilities, AI holds broad application prospects in the field of clinical pharmacy. This article introduces the current progress in AI applications within clinical pharmacy, focusing on its use in enhancing drug efficacy and safety. These applications include: assisting drug selection, optimizing dosage and administration timing, providing intelligent pharmaceutical services, predicting drug-drug interactions, pharmacovigilance, and preventing medication errors. Building on a review of current advancements, the article also discusses the challenges faced in implementing these AI applications. It proposes potential solutions, aiming to provide a reference for subsequent research and relevant practitioners.

     

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