MACROSCOPE
An Engineering Approach to Translational Medicine
Physician-scientists may benefit from an approach that emphasizes solving problems over generating hypotheses
Michael Liebman
Aging as a Background to Disease
The breast changes between a woman's time in utero and her
post-menopausal years. This maturation process is different for
women who have had children than for those who have not, and it also
varies under the influence of several variables: age of menarche,
use of hormonal birth control, number and timing of children, the
practice of breastfeeding, age of menopause and use of
hormone-replacement therapy. Thus, our definition of
"normal" varies with age and experience, and an optimal
diagnosis must use a systems-based approach to compare an individual
cancer patient's baseline (which we must guess at) to her disease
state (which we can measure during diagnosis and treatment). The
immediate aim of our project is to determine background levels of
gene and protein expression in breast tissue and to find out how
these numbers vary in a healthy population. This information will be
a significant step in the development of molecular diagnostics.
Note that a woman's life stages are not separated by fixed
boundaries. Rather, each represents a unique intersection of a
woman's age and an event. Given this complexity, it was crucial to
sieve the scientific literature for data that we could integrate
into a systems approach. This was more difficult than one might
think. Scientists have studied these stages for decades, producing a
tremendous body of work in physiology and pathology—more than
any one scientist can master. Furthermore, we recognized that even
the most encyclopedic and fair-minded review article cannot escape
the inherent bias of its author. Thus, we have harnessed some
computing power, employing text data-mining to cull the literature.
This effort has two aims: to refine the definitions of these stages
and to extract information about the underlying physiological and
developmental changes. This information becomes the foundation for
our molecular analyses and helps integrate clinical and molecular
data. We plan to augment this computational approach with a
community-based longitudinal study that includes molecular and
behavioral components.
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