Personalized Medicine - Translational Informatics: Realizing the Promise of Knowledge-Driven Healthcare - page 42

Fig. 3.5 The cost of health
care is far lower for
interventions performed
before a person falls ill

Pre-
symptomatic

Healthy Disease End of Life

Time

and procedures that are required once disease has set in (see Fig. 3.5 ). The ability to
target interventions based on who is at risk for a given disease, and ideally to pre-
vent the disease from manifesting in the fi rst place, would signifi cantly raise an
individual's quality of life and also lower health care costs. To this end, personalized
medicine aims to detect individuals who are at risk for a particular disease so that,
for example, diet and lifestyle may be changed before a high risk person has a heart
attack at age 45. Of course, everyone knows that exercise and a healthy diet are
benefi cial to one's health, and yet few people practice these guidelines. Studies are
ongoing to detect whether knowledge of one's personal risk provide the additional
motivation required to catalyze actual change [ 20 ].

3.4 Translational Bioinformatics in Personalized Medicine

The American Medical Informatics Association (AMIA) defi nes Translational
Bioinformatics as “the development of storage, analytic, and interpretive methods
to optimize the transformation of increasingly voluminous biomedical data, and
genomic data, into proactive, predictive, preventive, and participatory health” [ 21 ].
It is clear, then, how TBI plays a critical role in personalized medicine, as described
above. We describe here some “hot topics” in personalized medicine for which TBI
methods play an integral role.

3.4.1 Pharmacogenomics (PGX)

One of the most successful areas of application for personalized medicine
approaches has been in pharmacogenomics, or how a person's genes affect his or
her response to drugs. Interestingly, while attempts to identify genes responsible
for specifi c diseases have been somewhat disappointing, genes affecting the body's
ability to process and metabolize drugs have been more readily discovered. This
may be in part because there has been selective pressure against disease-risk genes