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Updated: Apr 26, 2026

Human Pluripotent Stem Cell Based Developmental Toxicity Assays for Chemical Safety Screening and Systems Biology Data Generation
Published on: June 17, 2015
Consensus report on the future of animal-free systemic toxicity testing
Marcel Leist1, Nina Hasiwa, Costanza Rovida
1Center for Alternatives to Animal Testing, CAAT-Europe, University of Konstanz, Konstanz, Germany.
Abstract:
Since March 2013, animal use for cosmetics testing for the European market has been banned. This requires a renewed view on risk assessment in this field. However, in other fields as well, traditional animal experimentation does not always satisfy requirements in safety testing, as the need for human-relevant information is ever increasing. A general strategy for animal-free test approaches was outlined by the US National Research Council`s vision document for Toxicity Testing in the 21st Century in 2007. It is now possible to provide a more defined roadmap on how to implement this vision for the four principal areas of systemic toxicity evaluation: repeat dose organ toxicity, carcinogenicity, reproductive toxicity and allergy induction (skin sensitization), as well as for the evaluation of toxicant metabolism (toxicokinetics) (Fig. 1). CAAT-Europe assembled experts from Europe, America and Asia to design a scientific roadmap for future risk assessment approaches and the outcome was then further discussed and refined in two consensus meetings with over 200 stakeholders. The key recommendations include: focusing on improving existing methods rather than favoring de novo design; combining hazard testing with toxicokinetics predictions; developing integrated test strategies; incorporating new high content endpoints to classical assays; evolving test validation procedures; promoting collaboration and data-sharing of different industrial sectors; integrating new disciplines, such as systems biology and high throughput screening; and involving regulators early on in the test development process. A focus on data quality, combined with increased attention to the scientific background of a test method, will be important drivers. Information from each test system should be mapped along adverse outcome pathways. Finally, quantitative information on all factors and key events will be fed into systems biology models that allow a probabilistic risk assessment with flexible adaptation to exposure scenarios and individual risk factors.
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