Toward Predicting Nanoparticle Distribution in Heterogeneous Tumor Tissues

Nanobio interaction studies have generated a significant amount of data. An important next step is to organize the data and design computational techniques to analyze the nanobio interactions. Here we developed a computational technique to correlate the nanoparticle spatial distribution within heter...

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Veröffentlicht in:Nano letters 2023-08, Vol.23 (15), p.7197-7205
Hauptverfasser: MacMillan, Presley, Syed, Abdullah M., Kingston, Benjamin R., Ngai, Jessica, Sindhwani, Shrey, Lin, Zachary P., Nguyen, Luan N. M., Ngo, Wayne, Mladjenovic, Stefan M., Ji, Qin, Blackadar, Colin, Chan, Warren C. W.
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Sprache:eng
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Zusammenfassung:Nanobio interaction studies have generated a significant amount of data. An important next step is to organize the data and design computational techniques to analyze the nanobio interactions. Here we developed a computational technique to correlate the nanoparticle spatial distribution within heterogeneous solid tumors. This approach led to greater than 88% predictive accuracy of nanoparticle location within a tumor tissue. This proof-of-concept study shows that tumor heterogeneity might be defined computationally by the patterns of biological structures within the tissue, enabling the identification of tumor patterns for nanoparticle accumulation.
ISSN:1530-6984
1530-6992
DOI:10.1021/acs.nanolett.3c02186