The H2020 Infrastructures project, NanoCommons, creates a community framework and infrastructure for reproducible science, and in particular for in silico workflows for nanomaterials safety assessment and beyond, by: 1. integration and federation of existing NMs characterisation and interaction mechanisms knowledge, protocols and data (beyond simple toxicity), along with quality assurance criteria and underpinning ontologies 2. compilation and development of a user-friendly interface for a suite of computational tools for mechanistic and statistical modelling, read-across, grouping, safe-by-design and life cycle assessment, and bench-marking of their predictive power; and 3. provision of (typically remote) access to its KnowledgeBase, modelling toolbox (predictive, grouping, risk assessment) and workflow optimisation, and the supporting expertise, to the broader user community.
NanoXtract is a unique online tool for the calculation of 18 image descriptors based on Transmission Electron Microscopy (TEM) images of nanomaterials.
This tool enables the generation of NInChI for a nanomaterial (NM) of preference, assuming that the NM is specified following the inside-to-outside structure approach.
This web service provides the functionality to predict the zeta-potential in water of individual or a set of engineered nanomaterials based on physicochemical and molecular properties.
Two predictive QNAR/kNN models for the assessment of decorated multi-walled carbon nanotubes (MWCNTs) biological and toxicological profile.
A kNN/read-across model for the prediction of nanomaterials (NMs) zeta-potential based on the NM type of core, main elongation and medium's pH value.
A predictive QNAR model of the cellular association of surface-modified gold nanoparticles (NPs) based on the acquired protein corona fingerprint and the NPs physicochemical properties.
This web application, hosted and implemented within Enalos Cloud Platform, estimates the risk of triggering AOP 173 (Lung Fibrosis) in mice due to exposure to 20nm TiO2 engineered nanoparticles.
This project has received funding from European Union Horizon 2020 Programme (H2020) via NanoCommons research infrastructure project under grant agreement nº 731032. More information at:
More information at: nanocommons.eu