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The number of newly engineered nanomaterials is vastly increasing along with their applications. Despite the fact that there is a lot of interest and effort is being put into the development of nano-based biomedical applications, the level of translational clinical output remains limited due to uncertainty in the toxicological profiles of the nanoparticles (NPs). As NPs used in biomedicines are likely to directly interact with cells and biomolecules, it is imperative to rule out any adverse effect before they can be safely applied. The initial screening for nanotoxicity is preferably performed in vitro, but extrapolation to the in vivo outcome remains very challenging. In addition, generated in vitro and in vivo data are often conflicting, which consolidates the in vitro-in vivo gap and impedes the formulation of unambiguous conclusions on NP toxicity. Consequently, more consistent and relevant in vitro and in vivo data need to be acquired in order to bridge this gap. This is in turn in conflict with the efforts to reduce the number of animals used for in vivo toxicity testing. Therefore the need for more reliable in vitro models with a higher predictive power, mimicking the in vivo environment more closely, becomes more prominent. In this review we will discuss the current paradigm and routine methods for nanotoxicity evaluation, and give an overview of adjustments that can be made to the cultivation systems in order to optimise current in vitro models. We will also describe various novel model systems and highlight future prospects.

Assessing nanoparticle toxicity in cell-based assays: influence of cell culture parameters and optimized models for bridging the in vitro–in vivo gap