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Challenges in using the ToxRefDB as a resource for toxicity prediction modeling.
Plunkett, Laura M; Kaplan, A Michael; Becker, Richard A.
  • Plunkett LM; Integrative Biostrategies, LLC, 1127 Eldridge Parkway, Suite 300-335, Houston, TX 77077, United States. Electronic address: lmplunkett@inbiostrat.com.
  • Kaplan AM; A. Michael Kaplan & Associates, LLC, 23 Wilkinson Drive, Landenberg, PA 19350, United States. Electronic address: amkaplan1@comcast.net.
  • Becker RA; American Chemistry Council, 700 Second Street NE, Washington, DC 20002, United States.
Regul Toxicol Pharmacol ; 72(3): 610-4, 2015 Aug.
Article en En | MEDLINE | ID: mdl-26003516
Developing and evaluating toxicity prediction models requires selection and use of datasets of known positive and negative agents for the endpoint(s) of interest. EPA's Toxicity Reference Database (ToxRefDB) is a publicly available dataset containing detailed study and effect information on more than 400 chemicals, and it has been used by EPA researchers to develop toxicity prediction models. During an initial evaluation of reproductive toxicity, however, limitations were uncovered in applying data from ToxRefDB that involved interpretation of toxicity effects and designation of toxicity endpoints, core attributes of the database that are critical to its use. These limitations for reproductive toxicity were found to be related, at least in part, to challenges faced in (1) evaluating the source of the original study data (EPA Data Evaluation Records (DERs)) for input into ToxRefDB and (2) interpretation of the biological significance of responses. These limitations of the ToxRefDB have important implications for the wider use of the database as it currently exists. Our results point to a need for improvements to the existing ToxRefDB and/or for researchers to independently evaluate, assign and verify positive or negative designations to data from ToxRefDB before use in development or validation of prediction models or testing frameworks.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Bases de Datos Factuales / Modelos Biológicos Tipo de estudio: Etiology_studies / Prognostic_studies / Risk_factors_studies Límite: Animals / Humans Idioma: En Año: 2015 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Bases de Datos Factuales / Modelos Biológicos Tipo de estudio: Etiology_studies / Prognostic_studies / Risk_factors_studies Límite: Animals / Humans Idioma: En Año: 2015 Tipo del documento: Article