In human risk assessment, time extrapolation factors (EFs) account for differences in exposure duration of experimental studies. We calculated EFs based on N(L)OEL (no (lowest) observed effect level) ratios, dividing shorter-term by longer-term values. The 'oral' datasets comprised 302 EFs (subacute-subchronic) and 1059 EFs (subchronic-chronic). The 'inhalation' datasets contained 67 EFs (subacute-subchronic) and 226 EFs (subchronic-chronic). The experimental EF distribution oral:subchronic-chronic showed that study parameters like deviation in dose selection and spacing influence mainly the data variance. Exclusion of these influences led to a dataset representing more realistically the difference of N(L)OELs with prolonged treatment. This dataset showed a GM of 1.5, indicating that the impact of a longer treatment period on the study N(L)OEL is on average not high. A factor of 1.5 seemed to be also sufficiently conservative for subacute-subchronic and subchronic-chronic extrapolation (inhalation or oral exposure). EFs for groups of similar compounds did not differ, but for compounds with low and high NOEL values. Relatively toxic compounds (GM 1) might thus not require time extrapolation. Within and between chemical variance was analysed in the dataset oral:subchronic-chronic (GSD 4.8). The variance between chemicals should be considered within extrapolation by selecting an appropriate percentile for which a chemical variance factor is suggested. In risk assessment, often a combination of EFs is required. Our analysis indicates that such a combination will result in an accumulation of non-toxicological variance and therefore unrealistically high EFs. Further evaluations are needed to identify appropriate chemical variance factors for these situations.
Keywords: Chronic; Data variance; EF distribution; Risk assessment; Subacute; Subchronic; Time extrapolation.
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