Detection of endpoints and biomarkers of repeated .. (DETECTIVE)
Detection of endpoints and biomarkers of repeated dose toxicity using in vitro systems
Date du début: 1 janv. 2011,
Date de fin: 31 déc. 2015
"Assessment of repeated dose toxicity is a standard requirement in human safety evaluation and relies on animal testing as no alternatives are currently accepted for regulatory purposes. An integrated research strategy for the replacement of animal tests needs to comprise the development of biomarkers of long-term toxicity in human target cells. To this aim, the DETECTIVE project will set up a screening pipeline of high content, high throughput as well as classical functional and “-omics” technologies to identify and investigate human biomarkers in cellular models for repeated dose in vitro testing. In view of industrial use in automated high throughput systems, essential questions of repeated dose toxicity such as stability and robustness of readouts will be investigated in a first phase. This will be the foundation for innovative biomarker development based on integration of multiple data streams derived from “-omics” readouts with traditional toxicological and histopathological endpoint evaluation. Toxicity pathways identified in “-omics” readouts can thus be further investigated by the functional readouts.DETECTIVE will initially use human hepatic, cardiac and renal models as common target organs of repeated dose toxicity. Ultimately, the strategy for establishing biomarkers will also be applicable to other organs or organ systems affected by systemic toxicants. It is also expected that DETECTIVE will be able to define human toxicity pathways relevant for all organs.Based on integrative statistical analysis, systematic verification and correlation with in vivo data, the most relevant, highly specific, sensitive and predictive biomarkers will be selected. Within DETECTIVE, partners from academia, industry and research will hence generate pathway- and evidence-based understanding of toxic effects, moving toxicology beyond descriptive science towards mechanism-based prediction."
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