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clinical development phases, and unfortunately have been an insidious cause of withdraw-
als post-market. Hepatic toxicology studies that have employed toxicogenomic technolo-
gies to date have already provided a proof-of-principle for the value of toxicogenomics in
drug discovery and development
[23]
and
[139-141]
. Notably, in most cases, gene expression
methodologies identified the differentially regulated genes that gave useful insight into the
mechanism of toxicity
[142-144]
. Beyond this application for interrogating mechanisms of
hepatotoxicity, toxicogenomics represent a viable approach for developing novel biomark-
ers that can be used as sensitive indicators of DILI. Hepatic toxicity is traditionally identi-
fied through the integrated evaluation of histopathological findings and clinical pathology
parameters, such as ALT and
/
or AST
[145]
. However, these changes often occur only after
prolonged periods of dosing, and may be too subtle to interpret in early, short-term stud-
ies
[146]
. In contrast, genomic biomarkers are frequently more sensitive than the traditional
functional and morphological markers
[147,148]
, providing the prospect of earlier detection
of hepatotoxicity in short-term studies, prior to full phenotypic manifestation.
As an example, acetaminophen (APAP) is a well-known hepatotoxicant and the most com-
mon cause of acute liver toxicity in Europe and the US
[135]
and
[149]
. The traditional bio-
markers such as ALT and AST are positive after pronounced liver injury has occurred. It is well
worth noting that diagnostic gene expression change in rat blood cells following APAP expo-
sure occurs well before liver damage can be diagnosed by classical parameters
[150]
. Further
study in humans with a low dose of APAP demonstrated that blood transcriptomics are suf-
ficiently sensitive and robust for prevention of liver injury, far outperforming classic clinical
chemistry tests
[23]
. The transcriptome may be a more effective marker or predictor for DILI
than other biomarkers. The use of transcript profiling for distinguishing classes of toxicity has
become well established
[34]
and
[151,152]
. Several toxicogenomics studies have monitored the
gene expression changes in the liver and
/
or the blood following exposure to hepatotoxicants.
6.4.3 Predictive Toxicology with Toxicogenomics
An early and reliable prediction of a drug candidate with potential to induce toxicity rep-
resents one of the major challenges in drug development. Toxicogenomics can inform the
drug development process by predicting an organism's response to a toxicant with genom-
ics. Predictive toxicogenomic studies usually compare the gene expression changes caused
by chemicals with unknown toxic potential to the profiles for model compounds with known
toxicity. To use toxicogenomics as a predictive tool, the prior knowledge of gene expres-
sion patterns related to toxicity is absolutely necessary. Currently, routine pre-clinical safety
assessment relies on a specific set of parameters consisting mainly of serum biochemistry,
hematology, and histopathology
[153]
. Unfortunately, some of these parameters are neither
sensitive nor specific enough for certain organ toxicities
[154,155]
. A means to overcome this
limitation is the integration of molecular profiling-based toxicogenomics technologies into
regular toxicological assessments. Specifically, global gene transcriptional profiling has the
potential to predict toxic responses under the principle that compounds that induce toxic-
ity through similar mechanisms will cause similar changes in gene expression patterns
[156]
. By grouping the gene expression profiles of well-characterized model compounds and
phenotypically anchoring these changes to conventional indices of toxicity, a gene expres-
sion signature or fingerprint related to specific organ toxicity could be generated and used
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