Toxicology of Industrial Compounds

13
Extrapolation of Toxicity Data and Assessment
of Risk
NORBERT FEDTKE
Hüls AG, Marl
Introduction
Risk assessment provides a link between scientific research and risk
management, or in other words, it is ‘a method for reaching public policy
decisions’ (Silbergeld, 1993). Risk assessment includes the key elements
hazard identification, dose-response assessment, and exposure assessment.
These elements are integrated in a risk characterization step to predict
adverse effects that may occur in a given population in a particular
exposure situation, often based on the quantification of the likelihood of this
occurrence. Risk management determines whether the particular exposure
situation presents an acceptable or unacceptable risk and whether it is
necessary to reduce the risk by reducing the exposure. Whereas risk
management has to account for public health, socio-economical factors,
technical feasibility, social perceptions, governmental policy and political
consequences, risk assessment should be based on scientific principles.
Since for the majority of industrial chemicals no or only limited human
data exist, the question of how to extrapolate the data obtained from
laboratory studies in experimental animals in order to predict the effects in
humans has become one important aspect in risk assessment. The final
goal is either to determine a level of exposure at which there is no reasonable
doubt that an adverse effect will not occur in man or to define the risk
associated with this exposure level. The use of mechanistic information to
provide linkages between exposure, dose to tissue, and biological responses
may assist in some of the steps necessary in the process of species
extrapolation. Especially the use of physiologically based pharmacokinetic
models (PBPK) for some aspects of risk assessment has been promoted to
reduce the uncertainty associated with the current default methods. PBPK
modeling is explained in general terms and a recently developed PBPK model
for 2-butoxyethanol is provided as an example to illustrate the use of
kinetic and mechanistic data in risk assessment.