OpenTox

OpenTox actively supports the development and validation of in silico model algorithms by improving the interoperability between individual systems (common standards for data and model exchange), increasing the reproducibility of in silico models (by providing a quality source of structures, toxicity data and algorithms) and by providing scientifically sound and easy-to-use validation routines.
OpenTox is a collaborative community project involving enterprise, university and government research groups. The mission is to carry out developments in an open and transparent manner from the early days of the project, and to open up discussions and development to the global community at large, who may either participate in developments or provide user perspectives.

OpenTox is working to meet the requirements of the REACH legislation using alternative testing methods to contribute to the reduction of animal experiments for toxicity testing.

Relevant international authorities (e.g. ECB, ECVAM, EPA and FDA) an industry organisations participate actively in the advisory board of the OpenTox project and provide input for the continuing development of requirement definitions and for model exchange.

Cooperation on data standards, data integration, ontologies, integration of algorithm predictions from different methods, and testing and validation all have significant collaboration opportunities and benefits for the community.

OpenTox actively supports the development and validation of in silico model algorithms by improving the interoperability between individual systems (common standards for data and model exchange), increasing the reproducibility of in silico models (by providing a quality source of structures, toxicity data and algorithms) and by providing scientifically sound and easy-to-use validation routines. 

OpenTox is committed to the support and integration of alternative testing methods using in vitro assay approaches, systems biology, stem cell technology, and the mining and analysis of human epidemiological data.

This page was updated on 04 March 2019
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