Revolutionising oral organoids with artificial intelligence.

Biomater Transl

Applied Oral Sciences and Community Dental Care, Faculty of Dentistry, The University of Hong Kong, Hong Kong Special Administrative Region, China.

Published: November 2024

The convergence of organoid technology and artificial intelligence (AI) is poised to revolutionise oral healthcare. Organoids - three-dimensional structures derived from human tissues - offer invaluable insights into the complex biology of diseases, allowing researchers to effectively study disease mechanisms and test therapeutic interventions in environments that closely mimic in vivo conditions. In this review, we first present the historical development of organoids and delve into the current types of oral organoids, focusing on their use in disease models, regeneration and microbiome intervention. We then compare single-source and multi-lineage oral organoids and assess the latest progress in bioprinted, vascularised and neural-integrated organoids. In the next part of the review, we highlight significant advancements in AI, emphasising how AI algorithms may potentially promote organoid development for early disease detection and diagnosis, personalised treatment, disease prediction and drug screening. However, our main finding is the identification of remaining challenges, such as data integration and the critical need for rigorous validation of AI algorithms to ensure their clinical reliability. Our main viewpoint is that current AI-enabled oral organoids are still limited in applications but, as we look to the future, we offer insights into the potential transformation of AI-integrated oral organoids in oral disease diagnosis, oral microbial interactions and drug discoveries. By synthesising these components, this review aims to provide a comprehensive perspective on the current state and future implications of AI-enabled oral organoids, emphasising their role in advancing oral healthcare and improving patient outcomes.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11764189PMC
http://dx.doi.org/10.12336/biomatertransl.2024.04.004DOI Listing

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