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The science behind the use of uncertainty factors has
progressed considerably. Increased knowledge of inter- and
intraspecies sensitivity, mechanisms of action, and detailed
evaluation of data bases can support the use of data-derived
uncertainty factors, which ultimately results in a risk
assessment with greater confidence. Papers that highlight
available data for each of several areas of uncertainty are
discussed, indicating that choice of the appropriate factor
requires scientific judgment on a case-by-case basis. Case
studies from EPA and Health Canada risk values illustrate the use
of data in chemical specific risk assessments to support the
selection of uncertainty factors other than the default value of
10-fold. In the case studies, the types of data that have been
used to support a change in the default value are explicitly
reviewed, as well as why the data support a different uncertainty
factor, how the uncertainty was reduced, and what assumptions
have been satisfied or replaced.
Incorporation of all available scientific data into the risk
assessment process fosters increased research and ultimately
reduces uncertainty. The results of this review support the use
of data-derived uncertainty factors when appropriate scientific
data are available.
To download the document, go here.
For more information, contact Dr. Michael Dourson at
513-542-7475, extension 14 or Dourson@tera.org.
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