Stem Cells and Organoids: A Paradigm Shift in Preclinical Models Toward Personalized Medicine - Eleanor Luce; Jean-Charles Duclos-Vallee (Pharmaceuticals, 2025)
Background/Objectives: Human pluripotent stem cells (hPSCs) and organoid technologies are transforming pharmaceutical research by providing models that more accurately reflect human physiology, genetic variability, and disease mechanisms. This review aims to assess how these systems improve the predictive power of preclinical drug development while addressing ethical concerns and supporting the advancement of precision medicine. Methods: We conducted a comprehensive review of the recent literature focusing on the biological principles, technological developments, and pharmaceutical applications of hPSC- and organoid-based systems. Particular attention was given to patient-derived models, integration of omics approaches, bioengineering advances, and artificial intelligence applications in drug screening workflows. Results: hPSC- and organoid-based platforms outperform traditional 2D cultures and animal models in replicating human-specific pathophysiology, enabling personalized drug testing and improving predictions of therapeutic efficacy and safety. These technologies also align with the ethical principles of the 3Rs (replacement, reduction, and refinement) by reducing reliance on animal experimentation. However, challenges persist, including standardization of protocols, batch-to-batch variability, and scalability. Promising solutions involve automation, high-throughput screening, and multi-omics integration, which collectively enhance reproducibility and translational relevance. Conclusions: Stem cell- and organoid-based systems offer a more human-relevant, ethical, and individualized approach to biomedical research. Despite current limitations, ongoing interdisciplinary innovations are expected to accelerate their clinical and industrial adoption. Collaborative efforts will be essential to standardize methodologies and fully realize the potential of these models in bridging preclinical and clinical drug development.