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Cancer Modeling‐on‐a‐Chip with Future Artificial Intelligence Integration
Author(s) -
Fetah Kirsten Lee,
DiPardo Benjamin J.,
Kongadzem EveMary,
Tomlinson James S.,
Elzagheid Adam,
Elmusrati Mohammed,
Khademhosseini Ali,
Ashammakhi Nureddin
Publication year - 2019
Publication title -
small
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.785
H-Index - 236
eISSN - 1613-6829
pISSN - 1613-6810
DOI - 10.1002/smll.201901985
Subject(s) - tumor microenvironment , cancer , cancer cell , stromal cell , drug development , cancer research , computer science , nanotechnology , biology , medicine , drug , tumor cells , materials science , pharmacology
Cancer is one of the leading causes of death worldwide, despite the large efforts to improve the understanding of cancer biology and development of treatments. The attempts to improve cancer treatment are limited by the complexity of the local milieu in which cancer cells exist. The tumor microenvironment (TME) consists of a diverse population of tumor cells and stromal cells with immune constituents, microvasculature, extracellular matrix components, and gradients of oxygen, nutrients, and growth factors. The TME is not recapitulated in traditional models used in cancer investigation, limiting the translation of preliminary findings to clinical practice. Advances in 3D cell culture, tissue engineering, and microfluidics have led to the development of “cancer‐on‐a‐chip” platforms that expand the ability to model the TME in vitro and allow for high‐throughput analysis. The advances in the development of cancer‐on‐a‐chip platforms, implications for drug development, challenges to leveraging this technology for improved cancer treatment, and future integration with artificial intelligence for improved predictive drug screening models are discussed.