Uncertainties in the Extrapolation of In Vitro Data in Human Risk Assessment: A Case Study of qIVIVE for Imazalil Using the Monte Carlo Risk Assessment Platform.

Abstract

New approach methodologies (NAMs) are promising for refining, reducing, and replacing animal experiments for hazard characterization. Quantitative in vitro-in vivo extrapolation (qIVIVE) is essential to extrapolate an in vitro-based point of departure to an in vitro-based human equivalent dose and subsequently to an in vitro-based health-based guidance or threshold value. The use of NAMs for hazard characterization leads to the need for various new extrapolations and linked uncertainties that preferably are quantified. Currently, qIVIVE is often performed without addressing these uncertainties. A clear description and, if possible, quantification of extrapolations and uncertainties when using NAMs for risk assessment will aid the regulatory implementation of NAMs for risk assessment. A case study of a qIVIVE-based assessment on the risk of liver steatosis from dietary exposure to imazalil is reported, using a human cell line in vitro test method as an example of a NAM to replace animal experiments. We consider the uncertainties related to the extrapolations from in vitro to in vivo effects, from in vitro nominal concentrations to in vitro intracellular concentrations, from in vitro concentrations to external doses (reverse dosimetry), from in vitro exposure durations to in vivo exposure situations, and from the average human to a sensitive individual. The case study addresses these uncertainties in a mainly quantitative approach, using available data and the Monte Carlo Risk Assessment platform.