Abstract
The inherent complexity and heterogeneity of tumors pose substantial challenges for the development of effective oncology therapeutics. Organoids, three-dimensional (3D) in vitro models, have become essential tools for predicting therapeutic responses and advancing precision oncology, with established correlations to clinical outcomes in patient-derived models. These systems have transformed preclinical drug screening by bridging the gap between conventional two-dimensional (2D) cultures and in vivo models, preserving tumor histopathology, cellular heterogeneity, and patient-specific molecular profiles. Despite their potential, limitations in tumor organoid biology, including inter-batch variability and microenvironmental simplification, can undermine their reliability and scalability in large-scale drug screening. To overcome these challenges, the integration of advanced technologies such as artificial intelligence (AI), automated biomanufacturing, multi-omics analytics, and vascularization strategies has been explored. This review highlights the "Organoid plus and minus" framework, which combines technological augmentation with culture system refinement to improve screening accuracy, throughput, and physiological relevance. We are convinced that the future of drug development hinges on the convergence of these multidisciplinary technologies with standardized biobanking and co-clinical validation frameworks. This integration will position organoids as a cornerstone for personalized drug discovery and therapeutic optimization, ultimately advancing the development of efficacy in oncology.