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Topic of biomarker
development and
application will be
explored through
discovery strategies
for biomarkers using
high throughput
omix technologies
and data integration with
clinical information.
We will outline the steps
for validating biomarkers
analytically and clinically
to ensure accuracy,
reliability, and
clinical relevance.
The talk will discuss
the main types
of biomarkers,
prognostic, predictive,
and pharmacodynamic
and their roles
in precision medicine
and treatment decisions.
Finally, we will examine
regulatory pathways
and the importance of
cross disciplinary
collaboration for
the adoption of biomarkers
into clinical practice.
Today, we'll explore how
biomarkers are discovered,
validated, and applied
in clinical practice.
Biomarkers are
measurable indicators
of biological processes,
disease states, or
therapy responses.
They can be molecules,
genes, proteins,
or physiological changes and
play a vital role in
precision medicine,
drug development,
and diagnostics.
Advances in OMIx and
digital health are
revolutionizing development,
but the field remains
complex and regulated.
Biomarker discovery often starts
with high throughput
OMIx platforms.
Genomics, transcriptomics,
proteomics and
metabolomics produce
comprehensive datasets
from clinical samples
like blood or tissue.
Computational methods and
machine learning identify
molecular patterns linked to
diseases or treatment responses.
Integrating these with
clinical datasets
ensures real world relevance.
