3D Bioprinting and Artificial Intelligence for Tumor Microenvironment Modeling: A Scoping Review of Models, Methods, and Integration Pathways
Piotrowska U., Tsoi J., Singh P., Banerjee A., Sobczak M.
Systematic Review, published in Mol Pharm (2025) — summary generated from the PubMed abstract.
Relatively higher-quality human studies compared with other topics in this database, e.g. multiple RCTs or systematic reviews. This does not mean it is standard or approved care.
- 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
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
- Systematic Review
- Journal
- Mol Pharm (2025)
- Reported sample size
- —
- Source database
- Europe PMC
- PMID
- 40964989
- PMCID
- PMC12505267
- DOI
- 10.1021/acs.molpharmaceut.5c01062
- Citations
- 10
Abstract (original English)
Recent advances in cancer research emphasize the development of physiologically relevant models to better understand tumor behavior and therapeutic responses. The tumor microenvironment (TME) plays a pivotal role in tumor progression, metastasis, and treatment resistance. Three-dimensional (3D) bioprinting offers unique capabilities for constructing complex in vitro tumor models that closely replicate the TME heterogeneity and interactions. These biomimetic models surpass the limitations of traditional 2D cultures and reduce the reliance on animal testing. This review aimed to systematically map current research on 3D bioprinting and artificial intelligence (AI) applications in modeling TME across selected cancer types. The review was structured into three thematic domains: 3D bioprinting of TME models for selected cancer types, AI applications in 3D bioprinting regardless of clinical focus, and integration of AI with 3D bioprinting specifically for TME modeling. A comprehensive literature search was conducted in PubMed, covering publications from January 2020 to June 2025. The review was conducted in accordance with PRISMA-ScR guidelines and focused on peer-reviewed original research articles published in English. Included cancer types were colorectal cancer, oral cancer, breast cancer, and glioma. In total, 63 articles were screened for TME-specific 3D bioprinting, with 44 in
What this study does not prove
- • This study does not prove SVF is an approved treatment or a replacement for standard care.
Evidence level
Relatively higher-quality human studies compared with other topics in this database, e.g. multiple RCTs or systematic reviews. This does not mean it is standard or approved care.
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