Shirzad Maryam, Salahvarzi Afsaneh, Razzaq Sobia, Javid-Naderi Mohammad Javad, Rahdar Abbas, Fathi-Karkan Sonia, Ghadami Azam, Kharaba Zelal, Romanholo Ferreira Luiz Fernando
Nanotechnology Research Center, Pharmaceutical Technology Institute, Mashhad University of Medical Sciences, Mashhad, Iran.
School of Pharmacy, University of Management and Technology, Lahore SPH, Punjab, Pakistan.
Crit Rev Oncol Hematol. 2025 Apr;208:104653. doi: 10.1016/j.critrevonc.2025.104653. Epub 2025 Feb 7.
Prostate cancer is one of the major health challenges in the world and needs novel therapeutic approaches to overcome the limitations of conventional treatment. This review delineates the transformative potential of artificial intelligence (AL) in enhancing nanocarrier-based drug delivery systems for prostate cancer therapy. With its ability to optimize nanocarrier design and predict drug delivery kinetics, AI has revolutionized personalized treatment planning in oncology. We discuss how AI can be integrated with nanotechnology to address challenges related to tumor heterogeneity, drug resistance, and systemic toxicity. Emphasis is placed on strong AI-driven advancements in the design of nanocarriers, structural optimization, targeting of ligands, and pharmacokinetics. We also give an overview of how AI can better predict toxicity, reduce costs, and enable personalized medicine. While challenges persist in the way of data accessibility, regulatory hurdles, and interactions with the immune system, future directions based on explainable AI (XAI) models, integration of multimodal data, and green nanocarrier designs promise to move the field forward. Convergence between AI and nanotechnology has been one key step toward safer, more effective, and patient-tailored cancer therapy.
前列腺癌是全球主要的健康挑战之一，需要新的治疗方法来克服传统治疗的局限性。本综述阐述了人工智能（AI）在增强用于前列腺癌治疗的基于纳米载体的药物递送系统方面的变革潜力。凭借其优化纳米载体设计和预测药物递送动力学的能力，人工智能彻底改变了肿瘤学中的个性化治疗方案规划。我们讨论了人工智能如何与纳米技术相结合，以应对与肿瘤异质性、耐药性和全身毒性相关的挑战。重点介绍了人工智能在纳米载体设计、结构优化、配体靶向和药代动力学方面的强大驱动进展。我们还概述了人工智能如何更好地预测毒性、降低成本并实现个性化医疗。尽管在数据可及性、监管障碍以及与免疫系统的相互作用方面仍然存在挑战，但基于可解释人工智能（XAI）模型、多模态数据整合和绿色纳米载体设计的未来方向有望推动该领域向前发展。人工智能与纳米技术的融合是迈向更安全、更有效且针对患者定制的癌症治疗的关键一步。
