Integrative Chemical–Biological Read-Across Approach for Chemical Hazard Classification

Traditional read-across approaches
typically rely on the chemical
similarity principle to predict chemical toxicity; however, the accuracy
of such predictions is often inadequate due to the underlying complex
mechanisms of toxicity. Here, we report on the development of a hazard
classification and visualization method that draws upon both chemical
structural similarity and comparisons of biological responses to chemicals
measured in multiple short-term assays (“biological”
similarity). The Chemical–Biological Read-Across (CBRA) approach
infers each compound’s toxicity from both chemical and biological
analogues whose similarities are determined by the Tanimoto coefficient.
Classification accuracy of CBRA was compared to that of classical
RA and other methods using chemical descriptors alone or in combination
with biological data. Different types of adverse effects (hepatotoxicity,
hepatocarcinogenicity, mutagenicity, and acute lethality) were classified
using several biological data types (gene expression profiling and
cytotoxicity screening). CBRA-based hazard classification exhibited
consistently high external classification accuracy and applicability
to diverse chemicals. Transparency of the CBRA approach is aided by
the use of radial plots that show the relative contribution of analogous
chemical and biological neighbors. Identification of both chemical
and biological features that give rise to the high accuracy of CBRA-based
toxicity prediction facilitates mechanistic interpretation of the
models.