The emergence of nanotechnology as a key enabling technology over the past years has
opened avenues for new and innovative applications in nanomedicine. From the business …

Robotics and automation provide potentially paradigm shifting improvements in the way
materials are synthesized and characterized, generating large, complex data sets that are …

Sustainable development is a key challenge for contemporary human societies; failure to
achieve sustainability could threaten human survival. In this review article, we illustrate how …

The quantitative adverse outcome pathway (qAOP) is proposed to inform dose-responses at
multiple biological levels for the purpose of toxicity prediction. So far, qAOP models …

The aquatic ecosystem is the final destination of most industrial residues and agrochemicals
resulting in organisms being exposed to a complex mixture of contaminants. Nanomaterials …

There is an urgent need to apply effective, data-driven approaches to reliably predict
engineered nanomaterial (ENM) toxicity. Here we introduce a predictive computational …

Machine learning has been an emerging scientific field serving the modern multidisciplinary
needs in the Materials Science and Manufacturing sector. The taxonomy and mapping of …

Mechanistic toxicology provides a powerful approach to inform on the safety of chemicals
and the development of safe‐by‐design compounds. Although toxicogenomics supports …

This research aims to review and evaluate the most relevant scientific studies about deep
learning (DL) models in the omics field. It also aims to realize the potential of DL techniques …

Abstract Ideally, a Systems Toxicology (ST) approach is aimed at by (eco) toxicologists, ie a
multidisciplinary area incorporating classical toxicological concepts with omics technologies …