Linanni Chen,1– 4,* Xinying Luo,1– 4,* Jiankang Zhang,1– 4 Jinwen Zhang,1– 4 Chunting Yang,1– 4 Yunqi Zhao1– 4 

1College of Science, Mathematics and Technology, Wenzhou-Kean University, Wenzhou, Zhejiang, People’s Republic of China; 2Wenzhou Municipal Key Laboratory for Applied Biomedical and Biopharmaceutical Informatics, Wenzhou-Kean University, Wenzhou, Zhejiang, People’s Republic of China; 3Zhejiang Bioinformatics International Science and Technology Cooperation Center, Wenzhou-Kean University, Wenzhou, Zhejiang, People’s Republic of China; 4Dorothy and George Hennings College of Science, Mathematics and Technology, Kean University, Union, NJ, USA

*These authors contributed equally to this work

Correspondence: Yunqi Zhao, College of Science, Mathematics and Technology, Wenzhou-Kean University, 88 Daxue Road, Wenzhou, Zhejiang, 325060, People’s Republic of China, Email yuzhao@kean.edu

Abstract: Cancer nanomedicine holds transformative potential, but its clinical translation remains hindered by the lack of preclinical models that accurately mimic human tumor complexity. Conventional approaches often overlook the dynamic tumor microenvironment (TME) and interpatient variability, leading to unreliable predictions of nanodrug behavior. Here, we present tumor organoids as a transformative solution. These three-dimensional cultures retain the original tumor’s architecture, molecular profiles, and TME interactions. Through concrete examples spanning pancreatic, breast, and glioblastoma cancers, we showcase how organoids reliably evaluate nanodrug delivery efficiency, therapeutic effects, and safety profiles. In addition, the establishment of large-scale organoid biobanks further facilitates rapid drug screening and tailored treatment strategies, significantly improving preclinical success rates. Therefore, the organoid-driven paradigm not only overcomes long-standing challenges in tumor modeling but also paves a faster, more reliable path toward clinically effective nanotherapies.

Keywords: cancer, drug screening, nanoparticle, organoid, personalized medicine