Combined in vitro-in vivo dosimetry enables the extrapolation of in vitro doses to human exposure levels: A proof of concept based on a meta-analysis of in vitro and in vivo titanium dioxide toxicity data

Abstract

Evaluating the potential risks of nanomaterials on human health is fundamental to assure their safety. To do so, Human Health Risk Assessment (HHRA) relies mostly on animal studies to provide information about nanomaterials toxicity. The scarcity of such data, due to the shift of the nanotoxicology field away from a phenomenological, animal-based approach and towards a mechanistic understanding based on in vitro studies, represents a challenge for HHRA. Implementing in vitro data in the HHRA methodology requires an extrapolation strategy; combining in vitro dosimetry and lung dosimetry can be an option to estimate the toxic effects on lung cells caused by inhaled nanomaterials. Since the two dosimetry models have rarely been used together, we developed a combined dosimetry model (CoDo) that estimates the air concentrations corresponding to the in vitro doses, extrapolating in this way in vitro doses to human doses. Applying the model to a data set of in vitro and in vivo toxicity data about titanium dioxide, we demonstrated CoDo's multiple applications. First, we confirmed that most in vitro doses are much higher than realistic human exposures, considering the Swiss Occupational Exposure Limit as benchmark. The comparison of the Benchmark Doses (BMD) extrapolated from in vitro and in vivo data, using the surface area dose metric, showed that despite both types of data had a quite wide range, animal data were overall more precise. The high variability of the results may be due both to the dis-homogeneity of the original data (different cell lines, particle properties, etc.) and to the high level of uncertainty in the extrapolation procedure caused by both model assumptions and experimental conditions. Moreover, while the surface area BMDs from studies on rodents and rodent cells were comparable, human co-cultures showed less susceptibility and had higher BMDs regardless of the titanium dioxide type. Last, a Support Vector Machine classification model built on the in vitro data set was able to predict the BMD-derived human exposure level range for viability effects based on the particle properties and experimental conditions with an accuracy of 85%, while for cytokine release in vitro and neutrophil influx in vivo the model had a lower performance.