The Synergistic Role of Artificial Intelligence and Nanotechnology in Precision Oncology – A Review

• Khalid AlBaimani

  Medical Oncology Department, Sultan Qaboos Comprehensive Cancer Care and Research, Muscat Oman.

• Omar Abdelhakim Ayaad

  Quality and Accreditation Department, Sultan Qaboos Comprehensive Cancer Care and Research Center, Muscat Oman.

• Meriem Khadraoui

  Medical Oncology Department, Sultan Qaboos Comprehensive Cancer Care and Research, Muscat Oman.

• Intissar Azzam Yehia

  Medical Oncology Department, Sultan Qaboos Comprehensive Cancer Care and Research, Muscat Oman.

• Ahmad Mohammad Matar

  Medical Oncology Department, Sultan Qaboos Comprehensive Cancer Care and Research, Muscat Oman.

• Zayana Talib AlKiyumi

  Nursing Department, Sultan Qaboos Comprehensive Cancer Care and Research Center, Muscat Oman.

• Nariman Mahmoud AbuHashish

  Nursing Department, Sultan Qaboos Comprehensive Cancer Care and Research Center, Muscat Oman.

Cancer persists as a predominant cause of mortality on a global scale, underscoring the imperative for ongoing advancements in treatment strategies. Cancer therapies, including chemotherapy, immunotherapy, and targeted therapy, have demonstrated efficacy; however, they are frequently associated with significant limitations, including tumor heterogeneity and adverse effects. The integration of artificial intelligence (AI) and nanotechnology has the potential to create a paradigm shift in the field of oncology, offering personalized and precise treatment modalities.

This review explores the role of artificial intelligence (AI) and nanotechnology in revolutionizing cancer care. A systematic review was conducted using databases such as Google Scholar, Springer Online, the Cochrane Library, and PubMed, employing keywords including "Cancer," "Artificial Intelligence," and "Nanotechnology." The selected studies include meta-analyses, randomized trials, and quasi-randomized studies, ensuring a comprehensive evaluation.

The findings underscore the potential of artificial intelligence (AI) to enhance diagnostic accuracy, predict nanomaterial toxicity, optimize drug delivery, and improve biomarker-based treatment planning. Moreover, artificial intelligence (AI)-driven methodologies, encompassing machine learning (ML) and deep learning (DL), enable personalized medicine by facilitating navigation and analysis of intricate oncological datasets. Concurrently, nanotechnology facilitates precise drug targeting, thereby enhancing treatment efficacy while minimizing systemic toxicity. The integration of artificial intelligence (AI) and nanomedicine presents a transformative approach to addressing drug resistance, predicting pharmacological responses, and refining patient-specific cancer therapies.

A number of challenges have been identified, including ethical concerns, data privacy issues, and the need for robust clinical validation. Future research should prioritize the integration of AI-driven nanomedicine into mainstream clinical practice, with a focus on ensuring its safety, efficacy, and accessibility for global oncology care.

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Copyright (c) 2025 Khalid AlBaimani, Omar Abdelhakim Ayaad, Meriem Khadraoui , Intissar Azzam Yehia , Ahmad Mohammad Matar , Zayana Talib AlKiyumi , Nariman Mahmoud AbuHashish

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