Artificial intelligence unlocks the future of oral organoid research

Abstract

Oral organoids, emerging as a powerful method for modeling oral development and diseases, show potential in fundamental research and clinical applications. However, their translational application in clinics is limited by low construction efficiency, labor-intensive data processing, and the complexity of integrating multi-omics data. Artificial intelligence (AI) offers promising solutions to overcome these limitations. AI-based robots can optimize culture conditions to enhance construction efficiency. Furthermore, AI enables the efficient analysis of organoid images and multi-omics data to elucidate underlying molecular mechanisms. The integration of oral organoids and AI could potentially overcome the limitations in organoid research and accelerate clinical translation. In this review, we first summarize the main types of oral organoids in the field and their construction strategies. Then, we introduce their application in regenerative medicine and the modeling of oral disease. We also examine the current limitations and discuss AI-based approaches to address these challenges, highlighting the critical role of AI in benefiting basic and translational oral research. • Revisits the history of oral organoid models. • Presents advancements and challenges in oral organoid models. • Discusses the potential of AI in accelerating clinical translation of oral organoid.