Publication Name	World Journal of Stem Cells
Manuscript ID	128748
DOI	10.4252/wjsc.128748
Country	China

Category	Cell & Tissue Engineering
Manuscript Type	Review
Article Title	Artificial intelligence-enabled virtual organoids: Digital-twin frameworks for predictive stem cell biology and precision regenerative medicine
Manuscript Source	Invited Manuscript
All Author List	Chen-Qi Zhang, Peng-Yu Yan, Hui-Fang Wang, Ya-Xiong Guo, Xiao Fan, Zheng-Dong Guo, Yu-Xiang Liu and Chun Liu
Funding Agency and Grant Number	Funding Agency Grant Number Young Scientists Fund of National Natural Science foundation of China 82305030 Fund Program for the Scientific Activities of Selected Returned Overseas Professionals in Shanxi Province 20260043
Corresponding Author	Chun Liu, Chief Physician, Consultant, Dean, Professor, Department of Urology, First Hospital of Shanxi Medical University, No. 85 Jiefang South Road, Taiyuan 030001, Shanxi Province, China. sxtyliuchun@126.com
Key Words	Artificial intelligence; Organoids; Digital twins; Stem cells; Regenerative medicine; Precision medicine; Multimodal data integration; Multiscale modelling
Core Tip	Artificial intelligence-enabled virtual organoids represent a proposed digital-twin framework that links physical organoids with dynamically updated computational models. This review defines their conceptual scope through five linked stages: Longitudinal multimodal observation, dynamic internal-state estimation, executable virtual-cell and hybrid multiscale modelling, prediction and virtual perturbation, and experimental validation with iterative updating. We further distinguish partial or early artificial intelligence-enabled virtual organoid prototypes, enabling technologies, and methodological precedents from complete virtual-organoid systems. We also discuss their potential applications in developmental biology, disease modelling, precision medicine, and regenerative medicine, together with key challenges in validation, uncertainty quantification, transferability, standardisation, and clinical translation.
Citation	Zhang CQ, Yan PY, Wang HF, Guo YX, Fan X, Guo ZD, Liu YX, Liu C. Artificial intelligence-enabled virtual organoids: Digital-twin frameworks for predictive stem cell biology and precision regenerative medicine. World J Stem Cells 2026; In press DOI: https://doi.org/10.4252/wjsc.128748
PDF	128748-in-press.pdf

Received	2026-09-28 13:17
Peer-Review Started	2026-09-28 13:18
First Decision by Editorial Office Director
Return for Revision	2026-10-08 06:10
Revised	2026-10-19 18:23
Publication Fee Transferred
Second Decision by Editor	2026-11-05 01:41
Second Decision by Editor-in-Chief
Final Decision by Editorial Office Director	2026-11-05 09:18
Articles in Press	2026-11-05 09:18
Edit the Manuscript by Language Editor
Typeset the Manuscript

ISSN	1948-0210 (online)
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