Publications by authors named "Panagiotis Isigonis"

Risk governance (RG) of nanomaterials (NMs) has been at the focus of the Horizon 2020 Programme of the European Union, through the funding of three research projects (Gov4Nano, NANORIGO, RISKGONE). The extensive collaboration of the three projects, in various scientific topics, aimed to enhance RG of NMs and provide a solid scientific basis for effective collaboration of the various types of stakeholders involved. In this paper the development of a digital Nano Risk Governance Portal (NRGP) and associated information technology (IT) infrastructure supporting the risk governance of (engineered) nanomaterials and nano-enabled products, is presented, alongside considerations for future work and enhancement within the domain of Advanced Materials (AdMa).

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The assessment of chemicals and materials has traditionally been fragmented, with health, environmental, social, and economic impacts evaluated independently. This disjointed approach limits the ability to capture trade-offs and synergies necessary for comprehensive decision-making under the Safe and Sustainable by Design (SSbD) framework. The EU INSIGHT project addresses this challenge by developing a novel computational framework for integrated impact assessment, based on the Impact Outcome Pathway (IOP) approach.

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Risk governance of nanomaterials and nanotechnologies is traditionally mainly limited to risk assessment, risk management and life cycle assessment. Recent approaches have experimented with widening the scope and including economic, social, and ethical aspects. This paper reports on tests and stakeholder feedback on the use of ethical impact assessment guidelines and tools adapting CEN Workshop Agreement part 2 CWA 17145-2:2017 (E)) to support risk governance of nanomaterials, in the RiskGONE project.

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The past few decades of managing the uncertain risks associated with nanomaterials have provided valuable insights (knowledge gaps, tools, methods, etc.) that are equally important to promote safe and sustainable development and use of advanced materials. Based on these insights, the current paper proposes several actions to optimize the risk and sustainability governance of advanced materials.

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A freely available "in vitro dosimetry" web application is presented enabling users to predict the concentration of nanomaterials reaching the cell surface, and therefore available for attachment and internalization, from initial dispersion concentrations. The web application is based on the distorted grid (DG) model for the dispersion of engineered nanoparticles (NPs) in culture medium used for in vitro cellular experiments, in accordance with previously published protocols for cellular dosimetry determination. A series of in vitro experiments for six different NPs, with Ag and Au cores, are performed to demonstrate the convenience of the web application for calculation of exposure concentrations of NPs.

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Nanotechnologies have reached maturity and market penetration that require nano-specific changes in legislation and harmonization among legislation domains, such as the amendments to REACH for nanomaterials (NMs) which came into force in 2020. Thus, an assessment of the components and regulatory boundaries of NMs risk governance is timely, alongside related methods and tools, as part of the global efforts to optimise nanosafety and integrate it into product design processes, via Safe(r)-by-Design (SbD) concepts. This paper provides an overview of the state-of-the-art regarding risk governance of NMs and lays out the theoretical basis for the development and implementation of an effective, trustworthy and transparent risk governance framework for NMs.

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Nanotechnology is a key enabling technology, which is developing fast and influences many aspects of life. Nanomaterials are already included in a broad range of products and industrial sectors. Nanosafety issues are still a matter of concern for policy makers and stakeholders, but currently, there is no platform where all stakeholders can meet and discuss these issues.

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Nanotechnology has enabled the discovery of a multitude of novel materials exhibiting unique physicochemical (PChem) properties compared to their bulk analogues. These properties have led to a rapidly increasing range of commercial applications; this, however, may come at a cost, if an association to long-term health and environmental risks is discovered or even just perceived. Many nanomaterials (NMs) have not yet had their potential adverse biological effects fully assessed, due to costs and time constraints associated with the experimental assessment, frequently involving animals.

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Nanotechnologies have been increasingly used in industrial applications and consumer products across several sectors, including construction, transportation, energy, and healthcare. The widespread application of these technologies has raised concerns regarding their environmental, health, societal, and economic impacts. This has led to the investment of enormous resources in Europe and beyond into the development of tools to facilitate the risk assessment and management of nanomaterials, and to inform more robust risk governance process.

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Ecotoxicological data are highly important for risk assessment processes and are used for deriving environmental quality criteria, which are enacted for assuring the good quality of waters, soils or sediments and achieving desirable environmental quality objectives. Therefore, it is of significant importance the evaluation of the reliability and relevance of available data for analysing their possible use in the aforementioned processes. In this context, a new methodology which has been developed based on Multi-Criteria Decision Analysis (MCDA) techniques, is being used, demonstrated and tested for analysing the reliability and relevance of ecotoxicological data of cyanide (which are produced through laboratory biotests for individual effects).

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Ecological Risk Assessment of chemicals in fluvial systems is a highly researched topic, but its importance for the environmental protection of our planet is vital. Thus, new developments and improvements to existing methodologies are proposed constantly, for providing more advanced tools and more accurate results to researchers and other interested parties. In the field of probabilistic Ecological Risk Assessment, a new Decision Support System is proposed, developed, tested and evaluated.

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Several tools to facilitate the risk assessment and management of manufactured nanomaterials (MN) have been developed. Most of them require input data on physicochemical properties, toxicity and scenario-specific exposure information. However, such data are yet not readily available, and tools that can handle data gaps in a structured way to ensure transparent risk analysis for industrial and regulatory decision making are needed.

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Ecotoxicological data are highly important for risk assessment processes and are used for deriving environmental quality criteria, which are enacted for assuring the good quality of waters, soils or sediments and achieving desirable environmental quality objectives. Therefore, it is of significant importance the evaluation of the reliability of available data for analysing their possible use in the aforementioned processes. The thorough analysis of currently available frameworks for the assessment of ecotoxicological data has led to the identification of significant flaws but at the same time various opportunities for improvement.

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Substantial limitations and uncertainties hinder the exposure assessment of engineered nanomaterials (ENMs). The present deficit of reliable measurements and models will inevitably lead in the near term to qualitative and uncertain exposure estimations, which may fail to support adequate risk assessment and management. Therefore it is necessary to complement the current toolset with user-friendly methods for near-term nanosafety evaluation.

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Hazard identification is an important step in assessing nanomaterial risk and is required under multiple regulatory frameworks in the US, Europe and worldwide. Given the emerging nature of the field and complexity of nanomaterials, multiple studies on even basic material properties often result in varying data pointing in different directions when data interpretation is attempted. Weight of evidence (WOE) evaluation has been recommended for nanomaterial risk assessment, but the majority of WOE frameworks are qualitative in nature and do not satisfy the growing needs for objectivity and transparency that are necessary for regulatory decision making.

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