Tumor‐on‐Chip Platforms for Precision Oncology: Bridging Tumor Heterogeneity and Preclinical Drug Testing

ABSTRACT Cancer drug development faces persistently low clinical success despite growing investment, mainly due to a translational gap driven by intratumoral heterogeneity, host‐tumor interactions, and resistance evolution. Tumor‐on‐chip platforms have emerged to bridge this gap by reconstructing human‐relevant microenvironments, yet current systems fall short in predictive power and scalability. Key limitations include: (i) incomplete tumor representation‐reliance on single‐line models, loss of stromal and immune diversity, and PDMS sorption‐induced dosing errors; (ii) workflow barriers‐non‐standardized fabrication, low throughput, endpoint‐biased analysis, and limited automation; and (iii) clinical integration issues‐restricted patient tissue access, lack of interoperable cryobank resources, and weak linkage to clinical outcomes. This review critically examines these challenges and proposes strategies such as modular biomimetic designs, immune‐stroma‐tumor co‐reconstitution using cryopreserved cells, standardized platforms with automated analytics, and cross‐validation with clinical or animal data to build regulatory confidence. We further discuss the impact of the FDA Modernization Act 2.0 and emerging market incentives driving non‐animal technologies. By coupling critique with pragmatic solutions, this review delineates a forward‐looking roadmap for advancing tumor‐on‐chip platforms into decision‐grade tools for precision oncology.