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Screening chemicals for potential neurotoxicity is hindered by lack of a relational database. A stakeholder group was formed to construct a publicly available, structure-searchable database to increase understanding of relationships between structure and neurotoxic activity. The goals are to: 1) enable data mining of biological and chemical information in relation to neurotoxicity; 2) provide a foundation for making chemical inferences and safety assessments; 3) construct a knowledge-base to support the development of in vitro and in silico methods for neurotoxicity assessment. The relational ToxML data model was adopted to enable query strategies for translating vast amounts of data into knowledge, such as neurotoxicity rules or alerts. Initially concentrating on DNT studies, a set of database fields and controlled vocabulary for neurotoxicity are proposed with the developmental model largely based on the ILSI RF Prototype developmental toxicity database: http://rsi.ilsi.org/Projects/devtoxsar.htm. In the ToxML database, a compound is represented hierarchically by studies, tests, dosage regimens and time lines, with maternal and offspring effects aggregated for each dose group. Offspring toxicity endpoints include functional tests, neurochemistry data, and neurohistopathology. As a pilot study, a limited number of publications were deconstructed and entered in the ToxML Editor. The resulting ToxML data model and controlled vocabulary are presented. The pilot DNT database is open and freely available (http://www.leadscope.com/toxml_editor) and provides a powerful tool for exploring biological and chemical elements relevant to the neurotoxic potential of chemicals (this abstract does not represent USEPA policy).

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This page is a summary of: Conversion of Developmental Neurotoxicity (DNT) information into a structure-searchable relational database, Neurotoxicology and Teratology, May 2008, Elsevier,
DOI: 10.1016/j.ntt.2008.03.034.
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