Hazard Assessment and Contaminated Sites - Dealing with Contaminated Sites: From Theory Towards Practical Application - page 552

dose-response curve for the carcinogenic response. Factors, such as genetic make-
up, lifestyle and other environmental factors, may also have a modifying influence
on the processes of carcinogenesis.

12.5.6 Mechanistically-Derived Models

These use models, which describe biological mechanisms by mathematical equa-
tions. They assume that the toxic effect results from the random occurrence of one
or more biological events. These are known as stochastic events (Klaassen 1996 ).
Examples of mechanistically-derived models are the One-hit, Log-probit, Weibull,
Linearised Multi-stage and Moolgavkar-Venson-Knudson models.
Mechanistically-derived models have been particularly used for cancer mod-
elling and especially those based on radiation exposures. The simplest form is a “one
hit” linear model in which only one “hit” or critical cellular interaction results in the
alteration of a cell. This model would propose that a single molecule of a genotoxic
carcinogen would have a “minute but finite chance of causing a mutational event”
(Klaassen 1996 ). From these models more complex models based on multihits or
multistage events have been derived. Although conceptually based on biological
mechanisms, most of these models do not rely on independently validated param-
eters describing the mechanisms, but rely on fitting curves to empirically observed
data.
More recently these models have been adapted to take into account information
based on knowledge of the relevant physiology and toxicokinetics (Physiologically-
based toxicokinetics (or pharmacokinetics) modelling). These models take into
account the effective dose at the target organ. A further development has been to
make generalised mechanistic models take into account specific biological pro-
cesses such as the Moolgavkar-Venson-Knudson model that uses a two-stage model
for carcinogenesis (Klaassen 1996 ).

12.5.7 Benchmark Dose Approach

The benchmark dose (BMD) approach has been used in dealing with both can-
cer and non-cancer end points. It is described in EHC170 and a modified version
for use with carcinogenic soil contaminants is described in “Toxicity Assessment
Guidelines for Carcinogenic Soil Contaminants” (NHMRC 1999 ). The benchmark
dose corresponds to a predetermined increase (usually 5%) of a defined effect in
a test population. Figure 12.4 illustrates how it is derived using a 5% increase.
Mathematically it is the statistical lower confidence limit on the dose that cor-
responds to that predetermined increase although some agencies are using a best
estimate rather than a lower confidence limit (IEH 1999 ).
In this example, LED 5 BD, and LED 5 is the lower confidence limit of the

effective dose causing a 5% increase in a defined effect.
For developmental toxicity the BMD 5 values have been similar to statistically-
derived NOAELs for a wide variety of developmental toxicity end points (Klaassen

=