Precision Pediatric Cancer Nanomedicine: Advancing Personalized Nano Therapies to Reduce Non-Communicable Diseases Through AI-Driven 3D-Printed Drugs

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.

Authors

Institutions

Publication Details

Journal
International Journal of Nanomedicine
Published
2026-02-01
DOI
https://doi.org/10.2147/ijn.s575214
Primary Topic
3D Printing in Biomedical Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Precision Pediatric Cancer Nanomedicine: Advancing Personalized Nano Therapies to Reduce Non-Communicable Diseases Through AI-Driven 3D-Printed Drugs

Mohamed Kchaou, Neeraj Choudhary, Dinesh Kumar, Thomas Webster et al.
International Journal of Nanomedicine
3D Printing in Biomedical Research
article

Precision Pediatric Cancer Nanomedicine: Advancing Personalized Nano Therapies to Reduce Non-Communicable Diseases Through AI-Driven 3D-Printed Drugs

Mohamed Kchaou, Neeraj Choudhary, Dinesh Kumar, Thomas Webster, Md Faiyazuddin, Thakur Jyoti, Bhupendra Prajapati
article en

Abstract

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.

International Journal of NanomedicineVol. Volume 21
Hebei University of Technology (CN), Brown University (US), Guru Kashi University (IN), GNA University (IN), Parul University (IN), University of Bisha (SA), Saveetha University (IN)
Openalex Percentile: Top 58%
3D Printing in Biomedical Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.