In:
Hepatology, Ovid Technologies (Wolters Kluwer Health), Vol. 65, No. 2 ( 2017-02), p. 710-721
Abstract:
Current preclinical drug testing does not predict some forms of adverse drug reactions in humans. Efforts at improving predictability of drug‐induced tissue injury in humans include using stem cell technology to generate human cells for screening for adverse effects of drugs in humans. The advent of induced pluripotent stem cells means that it may ultimately be possible to develop personalized toxicology to determine interindividual susceptibility to adverse drug reactions. However, the complexity of idiosyncratic drug‐induced liver injury means that no current single‐cell model, whether of primary liver tissue origin, from liver cell lines, or derived from stem cells, adequately emulates what is believed to occur during human drug‐induced liver injury. Nevertheless, a single‐cell model of a human hepatocyte which emulates key features of a hepatocyte is likely to be valuable in assessing potential chemical risk; furthermore, understanding how to generate a relevant hepatocyte will also be critical to efforts to build complex multicellular models of the liver. Currently, hepatocyte‐like cells differentiated from stem cells still fall short of recapitulating the full mature hepatocellular phenotype. Therefore, we convened a number of experts from the areas of preclinical and clinical hepatotoxicity and safety assessment, from industry, academia, and regulatory bodies, to specifically explore the application of stem cells in hepatotoxicity safety assessment and to make recommendations for the way forward. In this short review, we particularly discuss the importance of benchmarking stem cell–derived hepatocyte‐like cells to their terminally differentiated human counterparts using defined phenotyping, to make sure the cells are relevant and comparable between labs, and outline why this process is essential before the cells are introduced into chemical safety assessment. (H epatology 2017;65:710‐721).
Type of Medium:
Online Resource
ISSN:
0270-9139
,
1527-3350
Language:
English
Publisher:
Ovid Technologies (Wolters Kluwer Health)
Publication Date:
2017
detail.hit.zdb_id:
1472120-X
