Neeraj Choudhary, Dinesh Kumar, Thakur Jyoti, Bhupendra Prajapati, Mohamed Kchaou, Thomas Webster, Md Faiyazuddin
Pediatric cancers (PC) require treatments that maintain cure rates while minimizing long-term toxicity and non-communicable diseases. Yet, conventional dosing, adult-oriented formulations, and high treatment burden remain major limitations in childhood cancer care. This review synthesizes the current evidence using artificial intelligence (AI) and 3D nano printing as emerging tools to support personalized pediatric oncology. A structured literature search of PubMed, Scopus, Web of Science, and Google Scholar (2005-2024) identified English-language studies related to pediatric cancer, nanomedicine (NM), 3D printing, precision dosing, and pharmacogenomics, and relevant findings were organized by cancer type, clinical application, and potential impact on toxicity, adherence, and survivorship. Across leukemia, neuroblastoma, brain tumors, bone sarcoma, and lymphoma, AI-supported platforms were found to improve individualized chemotherapy exposure, anticipate toxicity based on clinical or pharmacogenomic markers, and assist clinicians towards modifying early treatment. At the same time, 3D nano printing enabled child-friendly medicines, multi-drug polypills, and controlled-release formulations that reduced dosing errors and improved treatment adherence. Early hospital-based experience with Bayesian therapeutic drug monitoring and on-demand pediatric drug printing suggested high feasibility for real clinical settings. Overall, AI-guided dosing and nano-printed formulations enhanced precision, lowering acute and late toxicities that support healthier long-term outcomes in children with cancer, particularly when linked to disease-specific needs. Further multicenter pediatric studies, regulatory development, and expansion of hospital 3D printing capacity are recommended to enable safe and equitable translation of these technologies into routine clinical care.