• Predicting Nanoparticle Toxicity using Animal-free Method
    In silico modeling of particle-cell interactions for the prediction of respiratory nanoparticle toxicity (graphical display). (credit: Helmholtz Zentrum München)
  • Tobias Stöger

News & Views

Predicting Nanoparticle Toxicity using Animal-free Method

Dec 31 2020

A novel animal-free method to predict the toxic effect of nanoparticles to the human lung has been developed by researchers at Helmholtz Zentrum München together with scientists across Europe. The method aims to enable the safety-by-design development of safer industrial materialsA team led by Dr. Tobias Stögerat at Helmholtz Zentrum München is focusing on an improved mechanistic understanding of the interactions between nanoparticles and lung cells, especially in view of the resulting inflammation which can lead to severe diseases with prolonged exposure.. In cooperation with partners from the SmartNanoTox EU project, the research group discovered that for certain materials the long-lasting inflammatory response to a single exposure to a nanoparticle can originate from two cellular key events which were so far unknown: First, the quarantining process which is the deposition of excreted immobile composites of the nanoparticles wrapped with biological molecules on the cell surface. Second, the so-called nanomaterial cycling which entails the movement of the nanoparticles between different alveolar lung cell types.
“With these new insights, we developed a deeper comprehensive approach on how an inflammatory response in the lung originates from particle-cell interactions. Being able to pinpoint the origin to these two key events and quantitatively describe them was a breakthrough as it helped us built our prediction method”, says Stöger.
Using only a small set of data from in vitro measurements and by combining it with in silico modeling, the researchers gathered insights on the toxicity of nanoparticles and managed to predict the spectrum of lung inflammation (from acute to chronic) associated with a range of 15 selected materials. Stöger adds: “Being able to make such a prediction means that we can move a step closer to a safe-by-design material development. This will have profound implications on the safety, speed and cost-effectiveness of new materials.”
This study introduces an alternative animal-free testing strategy capable for high-throughput testing and connectable with in silico modelling.
Original publication: Kokot et al., 2020: Prediction of Chronic Inflammation for Inhaled Particles, the Impact of Material Cycling and Quarantining in the Lung Epithelium. Advanced Materials, OI:10.1002/adma.202003913

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