Biomedical Engineering Reference
In-Depth Information
Where and when experimental testing of toxicity is expensive or
unnecessary, experimental data may under certain conditions be
complemented by alternative methods. Among these alternative methods
are computational tools, such as read-across and (Q)SAR, that can
predict a wide variety of toxicological properties. A good coverage of
predictions with different alternative models can help provide reasonable
estimations for the toxicity of a compound.
Such predictive toxicology draws knowledge from many independent
sources, which need to be integrated to provide a weight of evidence on
the toxicity of untested chemical compounds. Typical sources include
in
vivo
and
in vitro
experimental databases such as ToxCast [2] and
SuperToxic [3], literature-derived databases, such as SIDER summarizing
adverse reactions [4], and also computational resources based on toxicity
data for other compounds including DSSTox [5]. And somehow all this
information should be aggregated and presented to the user in such a way
that the various, potentially contradictory, pieces of information can help
reach a weighted decision on the toxicity of the compound.
Visualization of this information is, therefore, an important tool, and
should preferably be linked to the chemical structure of the compound
itself. Further visualization that will be important is that of relevant life
science data, such as gene, protein and biological pathway information
[6-8] or metabolic reactions [9]. Bioclipse was designed to provide such
interactive data analysis for the life sciences, although the resources are
not yet as tightly integrated as other sources.
Underlying this knowledge integration, there must be a platform that
allows researchers to use multiple prediction services. This is exactly
what the recently introduced Bioclipse-OpenTox platform is providing
[10]. This chapter will describe how this platform can be used to
interactively study the toxicity of chemical structures using computational
toxicology tools. Its ability to interactively predict toxicity and the ability
to dynamically discover computational services, allows users to get the
latest insights into toxicity predictions while hiding technicalities. Other
tools that provide similar functionality include the OECD QSAR ToolBox
[11] and ToxTree [12-13]. Bioclipse, however, is not a platform targeted
at toxicity alone, and has been used for other scientifi c fi elds too, taking
advantage of the ease by which other functionality, both local and remote,
can be integrated [14-16].
This chapter will not go into too much technical detail, but instead
provide two example use cases of the platform. Detailed descriptions can
be found in the papers describing the OpenTox Application Programming
Interface (API) [17] and the AMBIT implementation of this API [18], the
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