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Precision Pediatric Cancer Nanomedicine: Advancing Personalized Nano Therapies to Reduce Non-Communicable Diseases
Neeraj Choudhary1, Dinesh Kumar1, Thakur Prava Jyoti2
1GNA School of Pharmacy, GNA University, Phagwara, Punjab, 144401, India.
Insights
Artificial intelligence (AI) and 3D nano printing offer personalized treatments for pediatric cancers (PC). These technologies improve drug precision and adherence, reducing toxicity and enhancing long-term outcomes for children with cancer.
Area of Science:
- Oncology
- Nanomedicine
- Digital Health
Background:
- Pediatric cancer treatments face challenges with conventional dosing, adult formulations, and high treatment burden.
- Minimizing long-term toxicity and non-communicable diseases is crucial for pediatric cancer cure rates.
Purpose of the Study:
- To review current evidence on artificial intelligence (AI) and 3D nano printing in personalized pediatric oncology.
- To synthesize findings on AI and 3D nano printing applications for improving pediatric cancer treatment efficacy and reducing toxicity.
Main Methods:
- Structured literature search of major databases (PubMed, Scopus, Web of Science, Google Scholar) from 2005-2024.
- Focused on pediatric cancer, nanomedicine, 3D printing, precision dosing, and pharmacogenomics.
- Organized findings by cancer type, clinical application, and impact on toxicity, adherence, and survivorship.
Main Results:
- AI platforms enhance individualized chemotherapy exposure and toxicity prediction using clinical/pharmacogenomic markers.
- 3D nano printing facilitates child-friendly, controlled-release formulations, reducing dosing errors and improving adherence.
- Bayesian therapeutic drug monitoring and on-demand printing show feasibility in clinical settings.
Conclusions:
- AI-guided dosing and nano-printed formulations improve precision, reducing acute and late toxicities in pediatric cancer.
- These technologies support healthier long-term outcomes by addressing disease-specific needs.
- Further multicenter studies and regulatory development are needed for routine clinical integration.
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.
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