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Development of improved QSAR models for predicting the outcome of the in vivo micronucleus genetic toxicity assay.
Yoo, Jae Wook; Kruhlak, Naomi L; Landry, Curran; Cross, Kevin P; Sedykh, Alexander; Stavitskaya, Lidiya.
Afiliación
  • Yoo JW; US Food and Drug Administration, Center for Drug Evaluation and Research, 10903 New Hampshire Ave, Silver Spring, MD, 20993, USA.
  • Kruhlak NL; US Food and Drug Administration, Center for Drug Evaluation and Research, 10903 New Hampshire Ave, Silver Spring, MD, 20993, USA.
  • Landry C; US Food and Drug Administration, Center for Drug Evaluation and Research, 10903 New Hampshire Ave, Silver Spring, MD, 20993, USA.
  • Cross KP; Leadscope Inc., 1393 Dublin Road, Columbus, OH, 43215, USA.
  • Sedykh A; Multicase Inc., 23811 Chagrin Boulevard, Suite 305, Beachwood, OH, 44122, USA.
  • Stavitskaya L; US Food and Drug Administration, Center for Drug Evaluation and Research, 10903 New Hampshire Ave, Silver Spring, MD, 20993, USA. Electronic address: lidiya.stavitskaya@fda.hhs.gov.
Regul Toxicol Pharmacol ; 113: 104620, 2020 Jun.
Article en En | MEDLINE | ID: mdl-32092371
ABSTRACT
All drugs entering clinical trials are expected to undergo a series of in vitro and in vivo genotoxicity tests as outlined in the International Council on Harmonization (ICH) S2 (R1) guidance. Among the standard battery of genotoxicity tests used for pharmaceuticals, the in vivo micronucleus assay, which measures the frequency of micronucleated cells mostly from blood or bone marrow, is recommended for detecting clastogens and aneugens. (Quantitative) structure-activity relationship [(Q)SAR] models may be used as early screening tools by pharmaceutical companies to assess genetic toxicity risk during drug candidate selection. Models can also provide decision support information during regulatory review as part of the weight-of-evidence when experimental data are insufficient. In the present study, two commercial (Q)SAR platforms were used to construct in vivo micronucleus models from a recently enhanced in-house database of non-proprietary study findings in mice. Cross-validated performance statistics for the new models showed sensitivity of up to 74% and negative predictivity of up to 86%. In addition, the models demonstrated cross-validated specificity of up to 77% and coverage of up to 94%. These new models will provide more reliable predictions and offer an investigational approach for drug safety assessment with regards to identifying potentially genotoxic compounds.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Preparaciones Farmacéuticas / Relación Estructura-Actividad Cuantitativa / Desarrollo de Medicamentos Tipo de estudio: Guideline / Prognostic_studies / Risk_factors_studies Límite: Animals Idioma: En Revista: Regul Toxicol Pharmacol Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Preparaciones Farmacéuticas / Relación Estructura-Actividad Cuantitativa / Desarrollo de Medicamentos Tipo de estudio: Guideline / Prognostic_studies / Risk_factors_studies Límite: Animals Idioma: En Revista: Regul Toxicol Pharmacol Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos
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