A valuable
approach to chemical safety assessment is the use of
read-across chemicals to provide safety data to support the assessment
of structurally similar chemicals. An inventory of over 6000 discrete
organic chemicals used as fragrance materials in consumer products
has been clustered into chemical class-based groups for efficient
search of read-across sources. We developed a robust, tiered system
for chemical classification based on (1) organic functional group,
(2) structural similarity and reactivity features of the hydrocarbon
skeletons, (3) predicted or experimentally verified Phase I and Phase
II metabolism, and (4) expert pruning to consider these variables
in the context of specific toxicity end points. The systematic combination
of these data yielded clusters, which may be visualized as a top-down
hierarchical clustering tree. In this tree, chemical classes are formed
at the highest level according to organic functional groups. Each
subsequent subcluster stemming from classes in this hierarchy of the
cluster is a chemical cluster defined by common organic functional
groups and close similarity in the hydrocarbon skeleton. By examining
the available experimental data for a toxicological endpoint within
each cluster, users can better identify potential read-across chemicals
to support safety assessments.