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Perspectives from the NanoSafety Modelling Cluster on the validation criteria for (Q)SAR models used in nanotechnology

  • Datos identificativos

    Identificador: imarina:5131915
    Handle: http://hdl.handle.net/20.500.11797/imarina5131915
  • Autores:

    Puzyn T., Jeliazkova N., Sarimveis H., Marchese Robinson R., Lobaskin V., Rallo R., Richarz A., Gajewicz A., Papadopulos M., Hastings J., Cronin M., Benfenati E., Fernández A.
  • Otros:

    Autor según el artículo: Puzyn T., Jeliazkova N., Sarimveis H., Marchese Robinson R., Lobaskin V., Rallo R., Richarz A., Gajewicz A., Papadopulos M., Hastings J., Cronin M., Benfenati E., Fernández A.
    Departamento: Enginyeria Informàtica i Matemàtiques Enginyeria Química
    Autor/es de la URV: Fernández Sabater, Alberto / Rallo Moyá, Roberto Jesús
    Palabras clave: Validation Risk-assessment Real external predictivity Quantitative structure-activity Qsar models Qsar Qntr Qnar Oxidative stress Nano-qsar Metal-oxide nanoparticles Conformal prediction Confidence-intervals Biological-activity Applicability domain qsar qntr qnar nano-qsar
    Resumen: Nanotechnology and the production of nanomaterials have been expanding rapidly in recent years. Since many types of engineered nanoparticles are suspected to be toxic to living organisms and to have a negative impact on the environment, the process of designing new nanoparticles and their applications must be accompanied by a thorough risk analysis. (Quantitative) Structure-Activity Relationship ([Q]SAR) modelling creates promising options among the available methods for the risk assessment. These in silico models can be used to predict a variety of properties, including the toxicity of newly designed nanoparticles. However, (Q)SAR models must be appropriately validated to ensure the clarity, consistency and reliability of predictions. This paper is a joint initiative from recently completed European research projects focused on developing (Q)SAR methodology for nanomaterials. The aim was to interpret and expand the guidance for the well-known "OECD Principles for the Validation, for Regulatory Purposes, of (Q)SAR Models", with reference to nano-(Q)SAR, and present our opinions on the criteria to be fulfilled for models developed for nanoparticles.
    Áreas temáticas: Toxicology Saúde coletiva Química Odontología Nutrição Medicine (miscellaneous) Medicina veterinaria Medicina iii Medicina ii Medicina i Materiais Interdisciplinar Food science & technology Food science Farmacia Ensino Engenharias iv Engenharias ii Enfermagem Educação física Ciências biológicas iii Ciências biológicas ii Ciências biológicas i Ciências ambientais Ciências agrárias i Ciência de alimentos Biotecnología Biodiversidade Astronomia / física
    Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/
    ISSN: 02786915
    Direcció de correo del autor: robert.rallo@urv.cat alberto.fernandez@urv.cat
    Identificador del autor: 0000-0003-3812-4458 0000-0002-1241-1646
    Fecha de alta del registro: 2023-02-18
    Versión del articulo depositado: info:eu-repo/semantics/acceptedVersion
    Enlace a la fuente original: https://www.sciencedirect.com/science/article/abs/pii/S0278691517305562
    URL Documento de licencia: http://repositori.urv.cat/ca/proteccio-de-dades/
    Referencia al articulo segun fuente origial: Food And Chemical Toxicology. 112 478-494
    Referencia de l'ítem segons les normes APA: Puzyn T., Jeliazkova N., Sarimveis H., Marchese Robinson R., Lobaskin V., Rallo R., Richarz A., Gajewicz A., Papadopulos M., Hastings J., Cronin M., B (2018). Perspectives from the NanoSafety Modelling Cluster on the validation criteria for (Q)SAR models used in nanotechnology. Food And Chemical Toxicology, 112(), 478-494. DOI: 10.1016/j.fct.2017.09.037
    DOI del artículo: 10.1016/j.fct.2017.09.037
    Entidad: Universitat Rovira i Virgili
    Año de publicación de la revista: 2018
    Tipo de publicación: Journal Publications
  • Palabras clave:

    Food Science,Food Science & Technology,Medicine (Miscellaneous),Toxicology
    Validation
    Risk-assessment
    Real external predictivity
    Quantitative structure-activity
    Qsar models
    Qsar
    Qntr
    Qnar
    Oxidative stress
    Nano-qsar
    Metal-oxide nanoparticles
    Conformal prediction
    Confidence-intervals
    Biological-activity
    Applicability domain
    qsar
    qntr
    qnar
    nano-qsar
    Toxicology
    Saúde coletiva
    Química
    Odontología
    Nutrição
    Medicine (miscellaneous)
    Medicina veterinaria
    Medicina iii
    Medicina ii
    Medicina i
    Materiais
    Interdisciplinar
    Food science & technology
    Food science
    Farmacia
    Ensino
    Engenharias iv
    Engenharias ii
    Enfermagem
    Educação física
    Ciências biológicas iii
    Ciências biológicas ii
    Ciências biológicas i
    Ciências ambientais
    Ciências agrárias i
    Ciência de alimentos
    Biotecnología
    Biodiversidade
    Astronomia / física
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