Innovating Works

GenoQSAR

Financiado
Genotoxicity prediction by means of QSAR methods for regulatory purposes
The concern to protect human health and the environment has prompted significant changes in EU regulation on chemical substances. The European Chemicals Agency (ECHA) plays the role in implementing the Registration, Evaluation, Au... The concern to protect human health and the environment has prompted significant changes in EU regulation on chemical substances. The European Chemicals Agency (ECHA) plays the role in implementing the Registration, Evaluation, Authorization and Restriction of Chemicals (REACH) legislation, that requires industry to evaluate the toxicity of chemical substances that are in use but have never been subjected to regulatory testing. REACH regulation has also raised strong criticism and concern from society and industrials because of ethical and economic reasons. The toxicity evaluation of chemicals requires costly, time-consuming and ethically questionable animal experiments. As consequence, this European regulation promotes scientific innovation and encourages the use of results generated by alternative methods, including especially non-testing methods (NTMs), also referred to as in silico tools. Among them, Quantitative Structure-Activity Relationships (QSAR) methods are one of the most recognized machine learning methods in drug design, toxicology, industrial and environmental chemistry. Nowadays, they can be included in integrated testing strategies (ITS), to provide information for hazard and risk assessment, classification and labelling. We propose the development of an ensemble of QSAR predictive models for several parameters related with the different kinds of genotoxicity damage. These chemoinformatic will be implemented on a proprietary computational technological platform. Particular attention will be also payed to the generation of models for nanomaterials, taking into account their high and growing impact nowadays on industry in general.The QSAR models and integration algorithms will be characterized by their reliability, and will be developed according to the rules set out by the OECD, therefore guaranteeing their validity in REACH. ver más
30/09/2023
173K€
Duración del proyecto: 30 meses Fecha Inicio: 2021-03-17
Fecha Fin: 2023-09-30

Línea de financiación: concedida

El organismo H2020 notifico la concesión del proyecto el día 2023-09-30
Línea de financiación objetivo El proyecto se financió a través de la siguiente ayuda:
Presupuesto El presupuesto total del proyecto asciende a 173K€
Líder del proyecto
PROTOQSAR 2000 1. investigación, desarrollo e innovación. 2. actividades científicas y técnicas
Perfil tecnológico TRL 4-5 782K