Influence of exposure time on toxicity—An overview. (29th April 2016)

• Record Type: Journal Article
• Authors: Connell, Des W.; Yu, Qiming J.; Verma, Vibha
• Is Part Of: Toxicology. Volume 355/356(2016)
• Page Start: 49
• Page End: 53
• Publication Date: 2016-04-29
• Subjects: Lethal concentrations -- Lethal dose -- Habers Rule -- Reduced Life Expectancy (RLE) model -- Life expectancy -- Fish; Toxicology -- Periodicals; Chemicals -- Physiological effect -- Periodicals; 615.9005
• DOI: 10.1016/j.tox.2016.05.015
• Languages: English
• ISSNs: 0300-483X

Abstract

Graphical abstract: Abstract: Data on toxicity of chemicals is usually reported as the LD50, or LC50, with the exposure time from experimental testing in the laboratory reported. But the exposure time is not considered to be a quantifiable variable which can be used to evaluate its importance in expressed toxicity, often described in general terms such as acute, chronic and so on. For the last hundred years Habers Rule has been successfully used to extrapolate from reported exposure times to other exposure times which may be needed for setting standards, health risk assessments and other applications. But it has limitations particularly in environmental applications where exposure levels are low and exposure times are relatively long. The Reduced Life Expectancy (RLE) model overcomes these problems and can be utilised under all exposure conditions. It can be expressed as ln(LT50) = −a (LC50) ν + b where the constants ν, a and b can be evaluated by fitting the model to experimental data on the LC50, and corresponding LT50, together with the Normal Life Expectancy (NLE) of the organism being considered as a data point when the LC50 is zero. The constant, ν, at a value of unity gives a linear relationship and where ν < 1 the relationship has a concave shape. In our extensive evaluations of the RLE model for fish, invertebrates and mammals involving 115 data sets and with a wide range of organic and inorganic toxicants the RLE model gave correlation coefficients of >0.8 with 107 sets of data. The RLE model can be used to extrapolate from a limited data set on exposure times and corresponding LT50 values to any exposure time and corresponding LT50 value. The discrepancy between Haber's Rule and RLE model increases as the exposure time increases.