Since its inception, the CompSafeNano has focused on creating predictive models that are presented as web-applications to maximize their general use and approachability, conducting detailed material studies, and expanding nanoinformatics knowledge for societal and regulatory benefits.
Key Activities and Achievements:
CompSafeNano has created models that consider the unique features of NMs—such as size, shape, surface properties, and composition—to simulate their behavior in various environments. These models predict how NMs interact with biological systems and the environment, aiding in toxicity and safety assessments. Notably, the project developed the NanoConstruct web tool, allowing users to digitally construct nanoparticles by specifying their attributes and uploading Crystallography Information Files (CIFs) for precise atomistic descriptor calculations. The properties of these in silico nanomaterials can then be utilized as input to other nanoinformatics approaches to predict cellular attachment toxicity and more.
The project employs advanced artificial intelligence (AI) and machine learning approaches to link NM structures with their potential impacts, identifying properties that could make certain NMs harmful. These models enable rapid, efficient material screening and suggest safer design choices early in the development process, reducing reliance on lengthy laboratory tests. Additionally, new image analysis methods were developed to enrich datasets for future structure-property relationship studies.
By integrating safety considerations into the NM design phase, CompSafeNano promotes a proactive approach to nanotechnology. Through case studies, the project demonstrated how modifying NM structures or compositions can reduce risks without compromising functionality. For example, the interactions between graphene oxide and environmental molecules like tannic acid and their combined effects on toxicity to aquatic species such as zebrafish embryos were explored. This research supports the creation of a safe-by-design library guiding material adjustments to mitigate potential risks.
The project is developing the CompSafeNano Cloud Platform, a user-friendly, cloud-based e-platform that provides access to various models and datasets related to NM safety. This platform facilitates real-time assessments for industries, researchers, and regulators, making risk evaluation more accessible to both technical and non-technical users.
CompSafeNano has initiated training programs to equip researchers and professionals with skills in using advanced models and tools. Workshops at events like MaterialsWeek 2024 and the Beilstein Nanotechnology Symposium offered hands-on sessions in molecular simulations and data modeling, fostering a knowledgeable workforce capable of handling NM safety and risk assessments.
To maximize impact, the project collaborates with other nanotechnology and informatics initiatives like WorldFAIR, DIAGONAL and newly started projects PINK and INSIGHT. These partnerships promote data exchange, tool sharing, and best practices, fostering a standardized approach to NM safety across Europe. Engagement with regulatory bodies, industries, and public stakeholders ensures alignment with real-world regulatory and societal needs.
Outcomes for Society and Industry:
CompSafeNano is establishing a more reliable, efficient, and accessible method to ensure NM safety. By providing easy-to-use models, offering training, and fostering industry collaboration, the project contributes to making nanotechnology advances safer for people and the environment. This approach supports industry in responsibly designing next-generation materials and assists regulatory bodies in streamlining safety assessments, enhancing public confidence and acceptance of nanotechnology.
