Abstract
In order to protect our environment and people from detrimental effects of chemicals we have employed a universal tool: the risk assessment. Traditionally, risk assessment relied upon data derived from animal studies. However, these tests are subject to several ethical considerations, they are expensive and time consuming. As such, generating
... read more
safety information for the thousands of commercial chemicals is unrealistic, not only due to the high demand in animal sacrifice, but also due to practical reasons. Additionally, a lot of data clearly show that toxicity testing in experimental animals cannot always predict toxic effects pertinent to humans. As such, the scientific premise behind animal models being the golden standard for assessing chemical safety appears flawed. The field of toxicology is moving towards the next generation risk assessment that will use the New Approach Methodologies (NAMs). Novel approaches to hazard characterization will be driven by well-designed in vitro assays and the development of mechanism-based biomarkers. These assays will help establishing the underlying biological mechanisms that can likely result in an in vivo adverse outcome, thereby facilitating the shift from apical endpoints at an organism level to mechanistically anchored endpoints. Relying on these methodologies for predicting toxicity presupposes to quantitatively relate in vitro readouts to in vivo responses, the so-called Quantitative In Vitro to In Vivo Extrapolation (QIVIVE). An effective framework for performing QIVIVE is provided with the application of physiologically based kinetic (PBK) modelling with reverse dosimetry. PBK models are computational approaches based on a mathematical representation of absorption, distribution, metabolism and elimination of chemicals in a whole organism after oral, dermal or inhalation intake. They can be run for various species (e.g. rat, human), of different life stages (e.g. childhood, elderly people) and selected populations (e.g. pregnant women). These models can be applied for predicting the in vivo external exposure that would produce chemical concentrations in the target tissue equivalent to the concentrations at which effects were observed with in vitro assays. Parameterization of the models is facilitated with the use of in vitro- and in silico-derived substance-specific characteristics. This dissertation presents case studies of QIVIVE with the implementation of PBK modeling with the aim of exploring their ‘know-how’ and with the hope of contributing in building confidence in the application of NAMs for regulatory purposes. Different examples of QIVIVE are described ranging from approaches using generic PBK models to approaches employing substance-specific models.
show less
