Level D· Scientific groundwork from lab and animal studiesNarrative ReviewEurope PMCOpen access

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

Choudhary N., Kumar D., Jyoti TP., Prajapati BG., Kchaou M., Webster TJ.

Narrative Review on Hip, published in Int J Nanomedicine (2026) — summary generated from the PubMed abstract.

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Level D· Scientific groundwork from lab and animal studiesEvidence level of this study

Evidence from laboratory and animal studies provides groundwork for understanding mechanisms and potential before human studies continue.

  • Level A · Stronger Clinical Evidence
  • Level B · Emerging clinical evidence with positive signals
  • Level C · Early human research exploring benefits
  • Level D · Scientific groundwork from lab and animal studies
  • Emerging · Emerging topic under active research
Read the A–D evidence level guide

This page is generated from the PubMed record. The Thai description is an automated summary of bibliographic fields and the abstract, not a full translation, and is not medical advice.

Study type
Narrative Review
Journal
Int J Nanomedicine (2026)
Reported sample size
—
Source database
Europe PMC
PMID
41717314
PMCID
PMC12915454
DOI
10.2147/ijn.s575214

Abstract (original English)

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 feas

What this study does not prove

  • • This study does not prove SVF is an approved treatment or a replacement for standard care.
  • • This is a narrative review: it collects no new patient data and does not systematically appraise evidence quality.

Evidence level

Evidence from laboratory and animal studies provides groundwork for understanding mechanisms and potential before human studies continue.

How we grade evidence
HumansNeoplasmsAntineoplastic AgentsPediatricsArtificial IntelligenceChildNanomedicinePrinting, Three-DimensionalPrecision MedicineNoncommunicable Diseases

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