Biology Reference
In-Depth Information
6.4.1 The Roles of Toxicogenomics in Drug Discovery and Development
Gene expression analysis applied to toxicology studies has often been used by the phar-
maceutical industry as a useful tool to identify safer drugs in a quicker, more cost-effective
manner. Monitoring gene expression through the dual approaches of transcriptomics (RNA
profiling) and proteomics (protein profiling) has become a key component in our efforts to
understand complex biological processes. From the molecular stratification of disease states
and the selection of potential drug targets, to patient selection and the confirmation of
engagement of pharmacology in clinical studies, we are seeing the impact of gene expres-
sion profiling across all phases of the drug discovery and development process
[112,115,116]
.
Studies have already demonstrated the benefits of applying gene expression profiling
towards drug safety evaluation, both for identifying the mechanisms underlying toxicity,
and for providing a means to identify safety liabilities early in the drug discovery process
[117,118]
. Furthermore, toxicogenomics has the potential to better identify and assess ADRs
of new drug candidates or marketed products in humans
[11]
. As depicted in
Fig. 6.1
, toxi-
cogenomics can greatly influence the drug development process by:
1.
increasing our knowledge of molecular mechanisms of toxicity and efficacy;
2.
identifying sensitive biomarkers for better monitoring compound toxicity in clinical trials;
3.
enabling more informed decisions regarding safety of compounds;
4.
enhancing the ability to extrapolate accurately between experimental animals and
humans in the context of risk assessment; and
5.
providing a better understanding of the influence of genetic variation on toxicological
outcomes.
6.4.2 Toxicogenomics Applications - A Liver-Dominated Field
The liver is one of the major organs for the synthesis and secretion of substances which
metabolize endogenous and exogenous materials. There has been a great deal of interest in
elucidating the predictive and mechanistic genomic biomarkers of hepatotoxicity
[119-121]
.
Serum alanine aminotransferase (ALT) or aspartate aminotransferase (AST) measurements
are typically used to monitor liver damage and classify samples into responders and non-
responders upon an exposure to a toxicant
[122]
. However, increases in the transaminase
are not good prognosticators of liver injury and as such, have limitations in their usage as
biomarkers. For instance, ALT measurements do not always correlate well with histopatho-
logical data. There are cases where the variation of the ALT measurements among samples
sharing the same necrosis severity score is large
[123]
. In a more practical approach, the
severity of liver injury is represented by a composite score that incorporates different meas-
urements or according to the similarity of the biological processes of the samples to reflect
a phenotypic representation of a toxicant effect
[123,124]
. To improve the predictability
of drug-induced liver injury (DILI), it is essential to combine the conventional approaches
with the emerging technologies of toxicogenomics. Currently, there does not exist any reli-
able strategy for preventing DILI
[125]
; treatment options are limited to discontinuing
the offending drug, supportive care, and transplantation for end-stage liver failure
[126]
.
Thus, it is crucial to develop methods that will detect potential hepatotoxicity among drug
candidates as early and as quickly as possible. A better prediction, characterization, and
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