Department of Pharmacy, Unit of Pharmacology and Toxicology, University of Genoa, Genoa, Italy.
Department of Pharmacy, Da Nang University of Medical Technology and Pharmacy, Da Nang, Vietnam.
Pharmacol Rep. 2023 Feb;75(1):3-18. doi: 10.1007/s43440-022-00445-1. Epub 2023 Jan 9.
Artificial intelligence (AI) is a machine science that can mimic human behaviour like intelligent analysis of data. AI functions with specialized algorithms and integrates with deep and machine learning. Living in the digital world can generate a huge amount of medical data every day. Therefore, we need an automated and reliable evaluation tool that can make decisions more accurately and faster. Machine learning has the potential to learn, understand and analyse the data used in healthcare systems. In the last few years, AI is known to be employed in various fields in pharmaceutical science especially in pharmacological research. It helps in the analysis of preclinical (laboratory animals) and clinical (in human) trial data. AI also plays important role in various processes such as drug discovery/manufacturing, diagnosis of big data for disease identification, personalized treatment, clinical trial research, radiotherapy, surgical robotics, smart electronic health records, and epidemic outbreak prediction. Moreover, AI has been used in the evaluation of biomarkers and diseases. In this review, we explain various models and general processes of machine learning and their role in pharmacological science. Therefore, AI with deep learning and machine learning could be relevant in pharmacological research.
人工智能（AI）是一门机器科学，可以模拟人类行为，如数据的智能分析。AI 具有专门的算法，并与深度学习和机器学习集成。生活在数字世界中，每天都会产生大量的医疗数据。因此，我们需要一个自动化和可靠的评估工具，能够更准确、更快地做出决策。机器学习有潜力学习、理解和分析医疗保健系统中使用的数据。在过去的几年中，人工智能已被应用于药物科学的各个领域，特别是在药理学研究中。它有助于分析临床前（实验室动物）和临床（人体）试验数据。人工智能在药物发现/制造、疾病识别的大数据诊断、个性化治疗、临床试验研究、放射治疗、手术机器人、智能电子健康记录和传染病爆发预测等各个过程中也发挥着重要作用。此外，人工智能还用于评估生物标志物和疾病。在这篇综述中，我们解释了机器学习的各种模型和一般过程及其在药理学中的作用。因此，深度学习和机器学习的人工智能可能与药理学研究相关。
