Abstract
Organoids and cells in organ-on-chip platforms replicate higher-level anatomical, physiological, or pathological states of tissues and organs. These technologies are widely regarded by academia, the pharmacological industry and regulators as key biomedical developments. To map advances in this emerging field, a meta-analysis based on a quality-controlled text-mining algorithm is performed. The analysis covers titles, keywords, and abstracts of categorized academic publications in the literature and preprint databases published after 2010. The algorithm identifies and tracks 149 and 107 organs or organ substructures modeled as organoids and organ-on-chip, respectively, stem cell sources, as well as 130 diseases, and 16 groups of organisms other than human and mouse in which organoid/organ-on-chip technology is applied. The meta-analysis illustrates changing diversity and focus in organoid/organ-on-chip research and captures its geographical distribution. The downloadable dataset provided is a robust framework for researchers to interrogate with their own questions.
Adv Healthc Mater. 2023
https://onlinelibrary.wiley.com/doi/10.1002/adhm.202301067
