RESUMEN

The emergence of nanoinformatics as a key component of nanotechnology and nanosafety assessment for the prediction of engineered nanomaterials (NMs) properties, interactions, and hazards, and for grouping and read-across to reduce reliance on animal testing, has put the spotlight firmly on the need for access to high-quality, curated datasets. To date, the focus has been around what constitutes data quality and completeness, on the development of minimum reporting standards, and on the FAIR (findable, accessible, interoperable, and reusable) data principles. However, moving from the theoretical realm to practical implementation requires human intervention, which will be facilitated by the definition of clear roles and responsibilities across the complete data lifecycle and a deeper appreciation of what metadata is, and how to capture and index it. Here, we demonstrate, using specific worked case studies, how to organise the nano-community efforts to define metadata schemas, by organising the data management cycle as a joint effort of all players (data creators, analysts, curators, managers, and customers) supervised by the newly defined role of data shepherd. We propose that once researchers understand their tasks and responsibilities, they will naturally apply the available tools. Two case studies are presented (modelling of particle agglomeration for dose metrics, and consensus for NM dissolution), along with a survey of the currently implemented metadata schema in existing nanosafety databases. We conclude by offering recommendations on the steps forward and the needed workflows for metadata capture to ensure FAIR nanosafety data.

RESUMEN

International efforts to promote predictive toxicology incorporate some form of modeling based on the regularities, insights, and hypotheses gained from analyzing laboratory studies compiled in databases. While there has been a broad commentary on definitions, metadata, and test methodologies, all necessary to establishing data repositories, there has been less on translating the resulting insights into computational models. The recent use of a computational model to support a recommended exposure limit for nanoparticulate silver is an opportunity to examine physiologically based toxicokinetics in terms of data availability, model verification and validation, and regulatory acceptance. The resulting suggestions align with findings from the EU-US Roadmap Nanoinformatics 2030 and the 2018 acceptance of a computational model by the European Food Safety Authority.

Asunto(s)

RESUMEN

Dissolution, translocation, and disposition have been shown to play a key role in the fate and effects of inhaled particles and fibers. Concepts that have been applied in the micron size range may be usefully applied to the nanoscale range, but new challenges are presented based on the small size and possible change in the dissolution:translocation relationship. The size of the component molecule itself may be on the nanoscale. Solute concentration, surface area, surface morphology, surface energy, dissolution layer properties, adsorbing species, and aggregation are relevant parameters in considering dissolution at the nanoscale. With regard to the etiopathology caused by these types of particulates, the metrics of dose (particle number, surface area, mass or shape) is not yet well defined. Analytical procedures for assessing dissolution and translocation include chemical assay and particle characterization. Leaching of substituents from particle surfaces may also be important. Compartmentalization within the respiratory tract may add another dimension of complexity. Dissolution may be a critical step for some nanoscale materials in determining fate in the environment and within the body. This review, combining aspects of particle toxicology, material science, and analytical chemistry, is intended to provide a useful basis for developing relevant dissolution assay(s) for nanoscale particles.

Asunto(s)