Tumor organoid platform design for drug response modeling: culture architecture, microenvironmental complexity, and AI-assisted readouts

  • Shin, Eun Ah; 
  • Jeong, Won-Cheol; 
  • Kim, Ye-Won; 
  • Kim, Ji Won; 
  • Park, Miso
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초록

Tumor organoids preserve the cellular heterogeneity and structural complexity of native tumors, providing robust platforms for mechanistic studies, preclinical drug testing, and translational oncology research. However, their predictive performance is not an intrinsic property of organoids. It is shaped by platform design, including culture format, matrix composition, medium formulation, and the extent of multicellular reconstruction. This review examines how these design variables influence model fidelity, reproducibility, tumor microenvironment reconstruction, and drug-response interpretation. We compare major culture formats and matrix systems, discuss strategies for incorporating stromal and immune components, and evaluate current and emerging uses of AI-assisted analysis for organoid-derived phenotypic data. Overall, this review highlights how integrated tumor organoid design can strengthen pharmacological modeling and oncology translation.

키워드

Tumor organoids; Cancer modeling; Multicellular assembloids; Artificial intelligence in organoid research; INTESTINAL STEM-CELL; EXTRACELLULAR-MATRIX; IN-VITRO; COLORECTAL-CANCER; DISEASE; GROWTH; BEHAVIOR
제목
Tumor organoid platform design for drug response modeling: culture architecture, microenvironmental complexity, and AI-assisted readouts
저자
Shin, Eun Ah; Jeong, Won-Cheol; Kim, Ye-Won; Kim, Ji Won; Park, Miso
DOI
10.1007/s12272-026-01626-9
발행일
2026-06
유형
Review
저널명
Archives of Pharmacal Research
권
49
호
6
페이지
755 ~ 780