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This overview addresses
target identification
in practice with
particular emphasis on the
foundational principles and
importance of target
identification in drug discovery,
including how
advances in OMIx and
computational methods have
modernized this step.
We will discuss large scale
data driven techniques
used to profile disease
related molecules and
pathways and
highlight tools like
RNA interference and ISPACAS
for functional validation
of candidate targets.
The integration of
pathway analyses and
systems biology
will be addressed,
showing how they enhance
target selection
by revealing key nodes
and interactions.
Finally, we will emphasize
the necessity of
rigorous target validation
through genetic,
chemical, and phenotypic
approaches to
ensure reliability and
minimize costly failures.
Target identification
is a foundational step
in drug discovery
and development.
It involves recognizing
biological entities, genes,
proteins or signaling pathways,
critical to a disease process,
making them potential points
of therapeutic intervention.
Occurring after
disease selection
and before target validation,
this step has become
more systematic and data
driven with advances in OMIC
and computational methods.
Effective target
identification improves
drug success and helps avoid
costly failures by focusing
research on tractable
disease relevant mechanisms.
Modern target
identification now uses
large scale OMIC approaches
such as genomics,
transcriptomics, proteomics
and metabolomics.
