Friends or foes: new platform to predict nanoparticle toxicity
Nanomaterials are touted for their unique physicochemical characteristics, typically attributed to their small size, large surface area, chemical composition, solubility, shape and aggregation. Their implications range across sectors from agriculture and engineering to materials science and medicine. But despite their advantageous properties compared to those of bulk materials, they could also trigger severe environmental and health consequences with use.
The pillars supporting sustainable nanomaterial production
“Predicting nanomaterial safety involves understanding the ultimate nature of what makes a material toxic. This requires significant understanding of all lifecycle stages of the engineered nanoparticles: source, fate, exposure, dose and response. All these are closely intertwined,” notes Miguel A. Bañares, professor at the CSIC Institute of Catalysis and Petrochemistry in Madrid and coordinator of the EU-funded NanoInformaTIX project. NanoInformaTIX unveiled a nanoinformatics tool that blends all these components to uncover what renders a nanomaterial toxic. “We first need to find out about the environmental fate of engineered nanoparticles, namely how they will behave when interacting with the environment: will they sediment or remain loose? Their environmental fate, in turn, allows determining the likelihood of human exposure and associated health risks depending on the amount (dose) interacting with cells and tissues. Ultimately, our physiology and the nanoparticles entry routes in our body largely determine nanomaterial distribution,” adds Bañares.
Overcoming data fragmentation in nanotoxicology
New study results are adding to the vast amount of data on physicochemical, toxicological and ecotoxicological properties of engineered nanoparticles generated over the last few decades. Yet, such data is largely dispersed. NanoInformaTIX web-based sustainable nanoinformatics framework integrates existing and emerging data into efficient, user-friendly interfaces to enhance accessibility and usability of the nanoinformatics models for industry, regulators and society. “We have utilised state-of-the-art computational tools stemming from different scientific fields to extract information that can be associated with nanotoxicology,” notes Bañares. For example, the platform integrates eNanoMapper, one of the largest data sources on nanomaterial toxicological properties.
Building a holistic picture of nanoparticle toxicity
“Our understanding of how nanoparticles interact with each other, the environment and cells/tissues in our body would be limited if we only added state-of-the-art (eco)toxicological data and models to our platform. We also need to know the rationale behind their behaviour,” highlights Bañares. To this end, part of the work focused on creating new models describing nanoparticles themselves, namely how their structure, shape and defects could determine their interactions with the environment and our cells. Importantly, these models were validated using specially designed experiments that largely help generating relevant toxicity descriptors. The new models and toxicity descriptors are crucial for developing exposure, biodistribution and dose-response models. The NanoInformaTIX platform also integrates safe-by-design models, helping minimise toxicity risks at the earliest stages of nanomaterial production. Ultimately, the tool uses experimental data to study surface reactivity and omics approaches to determine adverse biological effects from nanoparticle-cell interactions. “On the one hand, we extracted data that would either be very challenging to obtain or costly to be generated by experiments. On the other hand, the combined use of tools and new models help enhance our understanding of the most fundamental mechanisms behind the toxicity of advanced engineered nanomaterials,” remarks Bañares.
Keywords
NanoInformaTIX, platform, nanoinformatics, engineered nanoparticles, nanoparticle toxicity, nanotoxicology, environmental fate, nanoparticle-cell interactions
