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On-Demand Generation of Patient-Derived Organoids for Precision Oncology: Progress and Prospects.

Created on 09 Oct 2026

Authors

Ziliang Guo, Shijie Yang, Keyu Shen, Yumeng Liu, Xiequn Xu

Published in

Advanced healthcare materials. Pages e71817. Oct 09, 2026. Epub Oct 09, 2026.

Abstract

Precision oncology has become a focus of both clinical practice and basic research. With the rapid evolution of organoid culture techniques and the integration of biomedical engineering approaches, patient-derived organoid (PDO) systems are playing an increasingly pivotal role in precision cancer therapy. By recapitulating patient-specific tumor characteristics, these platforms demonstrate considerable potential for clinical translation. Despite remarkable progress, the impact of PDO models on real-world therapeutic decision-making remains limited. Most existing studies have focused on preclinical concept validations or small-scale trials, leaving a substantial gap before these models can be implemented to guide individualized cancer therapy. This review examines on-demand PDO generation through the selection of sample-processing methods, matrices, and platform architectures matched to specific treatment-response questions. We compare conventional and engineered systems in terms of biological complexity, sample requirements, reported timelines, assay readouts, and clinical evidence. Particular attention is given to engineering trade-offs and the distinction between technical feasibility, clinical response correlation, and demonstrated utility in treatment selection.

PMID:
42851171
Bibliographic data and abstract were imported from PubMed on 09 Oct 2026.

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