• Delivering analytical and characterisation excellence in nanomaterial risk assessment: a tiered approach

    Delivering analytical and characterisation excellence in nanomaterial risk assessment: a tiered approach

  • Introducing confidence, adaptability and clarity into nanomaterial risk assessment

    Introducing confidence, adaptability and clarity into nanomaterial risk assessment

  • Facilitating decision-making in choice of techniques and SOPs

    Facilitating decision-making in choice of techniques and SOPs

ACEnano Knowledge Infrastructure publicly available to the scientific community

Collect, analyse and share nanomaterials physicochemical characterisation protocols and datasets

Web: https://acenano.douglasconnect.com/

Background

The ACEnano project (“Analytical and Characterisation Excellence in nanomaterial risk assessment: A tiered approach”) aims to develop a widely implementable and robust tiered approach to nanomaterials physicochemical characterisation. Read more about ACEnano at http://www.acenano-project.eu/. To showcase the capabilities of standardised but also newly emerging methods, several protocols and datasets are created by specialised laboratories. The ACEnano knowledge infrastructure (KI) was specifically designed to store and share these protocols and data and, finally, to become the standard repository for physicochemical data.

The ACEnano knowledge infrastructure (KI) supports all activities related to data collection. It provides a central place to access harmonised and standardised methods and data, supporting the implementation of Findable, Accessible, Interoperable and Reusable (FAIR) data principles, the reproducibility and documentation process towards the goal of generating reference resources for nanomaterials risk assessment.

It addresses, on the one hand, the needs of method developers (e.g., instruments providers, laboratories working on new methods) that aim to store, optimise and validate their protocols and, on the other hand, the needs of methods applicants (e.g., industry or research laboratories) that wish to have access to existing procedures, workflows and datasets in order to apply similar approaches and evaluate them regarding their performance, applicability domain and reproducibility. Similarly, the laboratories applying additional methods (e.g., functionalisation of nanomaterials), performing safety or toxicity assessments or using computational modelling to further analyse the data, require also access to harmonised physicochemical characterisation data. Finally, the aim of the knowledge infrastructure is to cover regulatory needs and the extraction of the information requested for the regulatory dossiers.

About the platform

The knowledge infrastructure of ACEnano accommodates data and protocols. The protocols database facilitates adding, sharing and comparing methods in a questionnaire-like format guiding users through the documentation process from starting material identification to sample preparation, measurement and data processing.

The data warehouse offers long-term storage of the results (data and a rich set of metadata) in a reusable format that are directly linked to the methods applied.

The experimental datasets of nanomaterials characterisation are stored together with relevant metadata pertaining to sample preparation, measurement and data treatment. By providing information that is as complete as possible, future use of the measured value is optimised.

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Overall, the functionality of the KI supports the implementation of Findable, Accessible, Interoperable and Reusable (FAIR) data principles, a transparent reproducibility and documentation process. The use of FAIR principles will generate reliable reference resources for nano materials risk assessment.

The new public version of the data warehouse available from 4 September 2019 is being integrated into the NanoCommons data ecosystem. By semantic annotation and linking, this guarantees harmonisation and interoperability with other data sources of the EU NanoSafety Cluster.

The development of the KI is supported by ACEnano (EU Horizon 2020 NMBP project no. 720952), while its availability to a wider community is assured by the activities in NanoCommons (Horizon 2020 INFRAIA project no. 731032).

 

In brief, this is how you can benefit from using this platform:

  • User-friendly platform, covering interlinked protocols and datasets in the area of physicochemical characterisation of nanomaterials;

  • Simple, data protected log-in system;

  • Add, store, consult or share protocols and procedures used for the physicochemical characterisation of nanomaterials;

  • Create a complete physicochemical characterisation workflow (sample preparation → measurement → data treatment);

  • Upload and download raw and processed datasets;

  • Harmonise the methodology within your organisations or projects;

  • Perform easily intra- and interlaboratory comparison of protocols and results towards achieving reproducibility and validation goals;

  • Automatically use data for analysis and computational modelling via the application programming interface (API);

  • Directly benefit from EdelweissDataTM technology (metadata integration, data searching, browsing and selection, data APIs selection, etc.);

  • Combine physicochemical data with other hazard and exposure data via linked data approaches based on common terminology and ontologies;

  • Use data and features of the platform for research, training or regulatory purposes;

  • Supports industry, CROs and consultants in regulatory dossiers preparation (e.g., under REACH regulation) by offering access to structured physicochemical characterisation information and datasets on different regulatory-relevant endpoints;

  • The platform is developed following the FAIR data principles.

     

    Endpoints covered: Average size dimension, Batch dispersion and stability, Crystalline phase, Density, Deposition rate, Elemental composition and chemical purity, Functional coating, Homoaggregation rate, Hydrophobicity, Isoelectric Point, NP-cell interaction, Particle Size Distribution, Particle number concentration, Particle shape, ROS generation, Redox speciation, Solubility/dissolution, Volume Specific Surface Area and Z-potential.

    (See details here: https://acenano.douglasconnect.com/protocols/techniques-endpoints/)

    Currently the Knowledge Infrastructure supports the area of physicochemical characterisation of nanomaterials, but we will extend its applicability to other domains. Many additional features will also be offered, including an advanced DataExplorer tool based on EdelweissDataTM technology and datasets citation using DOIs.

     

Documentation and training materials

Contact

  • For user support, business enquiries or feedback, please contact us at This email address is being protected from spambots. You need JavaScript enabled to view it.

     

Next training sessions

  • Information and hands-on sessions organised during the ‘EU NanoSafety Cluster Week’ (10 October 2019, Copenhagen, Denmark)

  • Demo session during the ‘OpenTox Euro’ Conference (29-31 October 2019, Basel, Switzerland)

 

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