Abstract

The historical reliance of biological research on the use of animal models has sometimes made it challenging to address questions that are specific to the understanding of human biology and disease. But with the advent of human organoids — which are stem cell-derived 3D culture systems — it is now possible to re-create the architecture and physiology of human organs in remarkable detail. Human organoids provide unique opportunities for the study of human disease and complement animal models. Human organoids have been used to study infectious diseases, genetic disorders and cancers through the genetic engineering of human stem cells, as well as directly when organoids are generated from patient biopsy samples. This Review discusses the applications, advantages and disadvantages of human organoids as models of development and disease and outlines the challenges that have to be overcome for organoids to be able to substantially reduce the need for animal experiments. Human organoids are valuable models for the study of development and disease and for drug discovery, thus complementing traditional animal models. The generation of organoids from patient biopsy samples has enabled researchers to study, for example, infectious diseases, genetic disorders and cancers. This Review discusses the advantages, disadvantages and future challenges of the use of organoids as models for human biology.

Keywords

OrganoidHuman diseaseComputational biologyBiologyDiseaseComputer scienceMedicineNeurosciencePathology

MeSH Terms

AnimalsBiologyCommunicable DiseasesGenetic DiseasesInbornGenetic EngineeringHumansMedicineNeoplasmsOrganoidsStem Cells

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Publication Info

Year
2020
Type
review
Volume
21
Issue
10
Pages
571-584
Citations
1917
Access
Closed

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1917
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Cite This

Jihoon Kim, Bon‐Kyoung Koo, Juergen A. Knoblich (2020). Human organoids: model systems for human biology and medicine. Nature Reviews Molecular Cell Biology , 21 (10) , 571-584. https://doi.org/10.1038/s41580-020-0259-3

Identifiers

DOI
10.1038/s41580-020-0259-3
PMID
32636524
PMCID
PMC7339799

Data Quality

Data completeness: 86%