Karimi-Sani Iman, Sharifi Mehrdad, Abolpour Nahid, Lotfi Mehrzad, Atapour Amir, Takhshid Mohammad-Ali, Sahebkar Amirhossein
Department of Medical Biotechnology, School of Advanced Medical Sciences and Technologies, Shiraz University of Medical Sciences, Shiraz, Iran.
Emergency Medicine Department, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran; Artificial Intelligence Department, Shiraz University of Medical Sciences, Shiraz, Iran.
Ageing Res Rev. 2025 Feb;104:102651. doi: 10.1016/j.arr.2024.102651. Epub 2025 Jan 2.
Parkinson's disease (PD) is one of the most incapacitating neurodegenerative diseases (NDDs). PD is the second most common NDD worldwide which affects approximately 1-2 percent of people over 65 years. It is an attractive pursuit for artificial intelligence (AI) to contribute to and evolve PD treatments through drug repositioning by repurposing existing drugs, shelved drugs, or even candidates that do not meet the criteria for clinical trials. A search was conducted in three databases Web of Science, Scopus, and PubMed. We reviewed the data related to the last years (1975-present) to identify those drugs currently being proposed for repositioning in PD. Moreover, we reviewed the present status of the computational approach, including AI/Machine Learning (AI/ML)-powered pharmaceutical discovery efforts and their implementation in PD treatment. It was found that the number of drug repositioning studies for PD has increased recently. Repositioning of drugs in PD is taking off, and scientific communities are increasingly interested in communicating its results and finding effective treatment alternatives for PD. A better chance of success in PD drug discovery has been made possible due to AI/ML algorithm advancements. In addition to the experimentation stage of drug discovery, it is also important to leverage AI in the planning stage of clinical trials to make them more effective. New AI-based models or solutions that increase the success rate of drug development are greatly needed.
帕金森病（PD）是最使人丧失能力的神经退行性疾病（NDDs）之一。PD是全球第二常见的神经退行性疾病，影响约1%至2%的65岁以上人群。通过重新利用现有药物、搁置药物甚至不符合临床试验标准的候选药物来进行药物重新定位，从而让人工智能（AI）为PD治疗做出贡献并推动其发展，这是一个很有吸引力的探索方向。我们在科学网、Scopus和PubMed这三个数据库中进行了检索。我们回顾了过去几年（1975年至今）的相关数据，以确定目前正在提议用于PD重新定位的药物。此外，我们还回顾了计算方法的现状，包括由人工智能/机器学习（AI/ML）驱动的药物研发工作及其在PD治疗中的应用。结果发现，最近针对PD的药物重新定位研究数量有所增加。PD药物的重新定位正在兴起，科学界越来越有兴趣交流其研究结果，并寻找PD的有效治疗替代方案。由于AI/ML算法的进步，PD药物研发成功的可能性更大。除了药物研发的实验阶段，在临床试验的规划阶段利用人工智能使其更有效也很重要。非常需要能够提高药物开发成功率的基于人工智能的新模型或解决方案。
