Biomedical Engineering Reference
In-Depth Information
Applications of 'omics data throughout the drug
discovery and development process
Figure 9.1
cell lines to discern patterns and signatures of mode of action. These can
later be utilized to discover interesting connections between drugs and
disease [3].
In the later phases of drug discovery, 'omics data can be utilized for
biomarker discovery and also increasingly to stratify patient populations.
A typical scenario is using pre-clinical species or cell line-based studies to
identify biomarkers using the lead compound, and then moving into the
clinic to validate the best candidate marker(s) to use in later trials. A
crucial application of a biomarker is to fi nd the optimum effi cacious dose
in humans, which in the past, was usually done by estimating downwards
from the maximum tolerated dose. This is not always the best approach,
as sometimes the maximum tolerated dose is not reached, so the best
dose may be much lower resulting in a safer drug. Many different 'omics
technologies can be utilized for biomarker discovery (see [4]), and there
is an increasing need for software that can integrate data from multiple
technologies.
There is also now an acute understanding that to truly treat human
disease, it is critical to study the disease as much as we can in humans.
Therefore, there is a large effort to do deep molecular profi ling of human
diseased samples, to gain a better understanding of disease
pathophysiology. Furthermore, it is important to also know target
expression and distribution in normal tissues to understand how the drug
will act on the body and to highlight any potential side effects early on.
It is therefore crucial that not only computational experts, but also
discovery bench scientists, clinicians, drug metabolism and
pharmacokinetics (DMPK) scientists and toxicologists can easily access
and interpret this type of data.
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