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Welcome to the
Endocrine Disruptor Knowledge Base

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The Endocrine Disruptor Knowledge Base (EDKB) website consists of a biological activity database, relevant literature citations, computational models, and ultimately, models for risk assessment. It is designed to help research and regulatory scientists, and other interested parties set priorities for testing of endocrine disrupting compounds, make use of the existing body of knowledge, and reduce dependency upon slow and expensive animal experiments.

Legislation requiring the development and implementation of a strategy for screening and testing chemicals for estrogen, androgen and thyroid endpoints [EDSTAC, #545] led to the definition of a two-tiered, multiple-endpoint strategy by EPA's Endocrine Disruptor Screening and Testing Advisory Committee (EDSTAC) of which FDA is a participating member. This strategy incorporates more than 20 different in vitro and in vivo assays [Gray, 1998 #250]. As many as 87,000 chemicals may need to be screened for endocrine-disruption potential [Patlak, 1996 #526]. The large number of chemicals (87,000) and assays makes it difficult for each chemical to be run through these assay batteries in a reasonable time. There is a crucial need for priority setting to identify the chemicals most likely to possess endocrine disrupting activity for early entry into screening.

The website provides access to a relational database comprising in vitro and in vivo experimental data. The front end of the database is a JAVA program developed to provide a powerful, flexible and friendly human interface to perform knowledge mining.

Endocrine disruptors are chemicals that interfere with the endocrine systems, leading to adverse effects. Some chemicals do this by binding to receptors, such as the estrogen and androgen receptors. Currently, most in vitro and in vivo data are derived from assays that measure estrogenic activity, and fewer data are for assays that measure androgen activity.

A major element of the EDKB program has been the development of computer-based predictive models to predict affinity for binding of compounds to the estrogen and androgen nuclear receptor proteins. These models have been developed using commercial, state-of-the-art chemometric, SAR and QSAR software packages that are commonly used in drug discovery and development. Hence, the models cannot be automated for use through this website. In the future, we may develop models that can be used online within the website.

For more indepth review of the EDKB program, the reader is referred to the program publications.

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