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Updated: May 20, 2026

Human Pluripotent Stem Cell Based Developmental Toxicity Assays for Chemical Safety Screening and Systems Biology Data Generation
Published on: June 17, 2015
Human pluripotent stem cells for modeling toxicity
R L C Sison-Young1, R Kia, J Heslop
1MRC Centre for Drug Safety Science, Department of Molecular and Clinical Pharmacology, University of Liverpool, Liverpool, United Kingdom.
Abstract:
The development of xenobiotics, driven by the demand for therapeutic, domestic and industrial uses continues to grow. However, along with this increasing demand is the risk of xenobiotic-induced toxicity. Currently, safety screening of xenobiotics uses a plethora of animal and in vitro model systems which have over the decades proven useful during compound development and for application in mechanistic studies of xenobiotic-induced toxicity. However, these assessments have proven to be animal-intensive and costly. More importantly, the prevalence of xenobiotic-induced toxicity is still significantly high, causing patient morbidity and mortality, and a costly impediment during drug development. This suggests that the current models for drug safety screening are not reliable in toxicity prediction, and the results not easily translatable to the clinic due to insensitive assays that do not recapitulate fully the complex phenotype of a functional cell type in vivo. Recent advances in the field of stem cell research have potentially allowed for a readily available source of metabolically competent cells for toxicity studies, derived using human pluripotent stem cells harnessed from embryos or reprogrammed from mature somatic cells. Pluripotent stem cell-derived cell types also allow for potential disease modeling in vitro for the purposes of drug toxicology and safety pharmacology, making this model possibly more predictive of drug toxicity compared with existing models. This article will review the advances and challenges of using human pluripotent stem cells for modeling metabolism and toxicity, and offer some perspectives as to where its future may lie.
Insights
Human pluripotent stem cells offer a promising alternative for predicting xenobiotic toxicity. These advanced models improve upon traditional methods, potentially reducing drug development costs and enhancing patient safety.
Area of Science:
- Biotechnology
- Toxicology
- Stem Cell Research
Background:
- The increasing development of xenobiotics for various uses necessitates robust toxicity screening.
- Current animal and in vitro models for xenobiotic safety assessment are costly, animal-intensive, and often lack clinical translatability.
- High rates of xenobiotic-induced toxicity contribute to patient morbidity and mortality, highlighting limitations in existing safety screening methods.
Purpose of the Study:
- To review the advancements in using human pluripotent stem cells (hPSCs) for modeling xenobiotic metabolism and toxicity.
- To discuss the challenges associated with hPSC-based toxicity studies.
- To provide perspectives on the future applications of hPSCs in drug toxicology and safety pharmacology.
Main Methods:
- Review of current literature on xenobiotic toxicity screening models.
- Exploration of human pluripotent stem cell technologies for generating metabolically competent cells.
- Analysis of hPSC-derived cell types for in vitro disease modeling in toxicology.
Main Results:
- Human pluripotent stem cells provide a renewable source of metabolically competent cells for toxicity testing.
- hPSC-derived models offer potential for more accurate prediction of drug toxicity compared to traditional methods.
- These models can be utilized for in vitro disease modeling relevant to drug toxicology.
Conclusions:
- Human pluripotent stem cells represent a significant advancement in developing more predictive models for xenobiotic metabolism and toxicity.
- Overcoming current challenges will be crucial for the widespread adoption of hPSC-based toxicity screening.
- Future research directions include refining hPSC differentiation protocols and validating their predictive capacity in drug safety assessment.
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