Comparing the toxicity from freshly dispersed NMs to the same NMs that have been stored for 2 years in artificial water of a different composition to the water flea Daphnia Magna.
NanoSolveIT H2020 researchers developed ecotoxicological read-across models to predict NMs acute toxicity.
— Antreas Afantitis
CYRPUS, February 4, 20, 222/EINPresswire.com/ — Although it has been almost 20 years since the first commercialization of nanomaterials, there are still many questions to be answered about their interactions with living organisms. A paper published in Elseviers Chemosphere (November 2016)https://doi.org/10.1016/j.chemosphere.2021.131452) compares the toxicity of freshly dispersed NMs with the same NMs stored for 2 years in artificial river waters of different composition (environmentally aged NMs) to the water flea Daphnia Magna. Researchers believed that older NMs might be more toxic than the fresh ones. However, they were proven right: NMs stored in both salt-only artificial rivers and river water containing both natural organic matter and salts caused less toxicity to the Daphnids than the newly dispersed NMs. This is due to the passivation of the surface reactivity.
Researchers from NovaMechanics LtdThe University of Birmingham and Ecotoxicological Read-Across Models for Predicting NMs Acute Toxicity were developed following the European Chemicals Agency’s recommendation. Combining widely accepted and accurate informatics tools such as the Isalos & KNIME Analytics Platforms, with the Enalos Cloud Platform, which allows for the manipulation of large data, the computational modeling process was achieved. The predictive power of the proposed Quantitative Activity Relationship (QSAR), models has been evaluated using the criteria set forth by the Organisation for Economic Cooperation and Development. A QSAR Model Reporting Format report (QMRF), has been prepared and made available in the supplementary data of the paper to facilitate regulatory acceptance and uptake. This study also produced Findable, Accessible, Interoperable, Reusable (FAIR), datasets that will be used by other scientists to further investigate the toxicity and prediction of environmentally aged NMs.
Professor of Environmental Nanosciences at University of Birmingham, Iseult Lynch, notes that it is a major regulatory challenge to develop reliable prediction models for NMs. It is impossible to experimentally evaluate all variants of NMs due time, cost, and ethical restrictions. Therefore, computational models utilizing regulatory-relevant species like D. Magna that can predict toxicity of data-poor NMs, such models are urgently required.
The new nanoinformatics models allow researchers to investigate in silico the effects on a panel of newly dispersed NMs versus those that have been aged for a while. This is a significant advance. Antreas Afantitis (Managing Director, NovaMechanics Ltd)www.novamechanics.com) and NanoSolveIT (www.nanosolveit.eu) Project Coordinatorhighlights that Nanoinformatics is an evolving field of research that includes the development of in silico models and tools that could be an alternative to the experimental evaluation of nanomaterials (NMs) environmental health and safety (exposure and toxicity) and thus contribute to NMs hazard and risk assessment.
The machine learning read-through model is available through NanoSolveIT Cloud Platform (https://ecotox.cloud.nanosolveit.eu/) and the full dataset is available through the nanoPharos (2021) database https://db.nanopharos.eu/Queries/Datasets.zul) developed under the H2020 NanoSolveIT and NanoCommons projects, in compliance with the FAIR data principles and is ready for further computational analysis.
Antreas Afantitis
NovaMechanics Ltd
+357 24 250440
[email protected]
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