The above statement is now
accepted by nearly all physicians and scientists despite the fact that exactly
how, and when, this revolution will occur remains far from clear. Unfortunately,
the long anticipated "genomic revolution" has yet to have a
significant impact on the daily practice of clinical medicine. The amount
of existing data on the human genome far exceeds the capacity of practicing
physicians to prioritize, validate and incorporate the available information
into medical practice.
The need for genomic
medicine is clear. The practice of medicine in 2007 remains
focused on the analysis of average individuals. For example, the average
person should exercise often, maintain their ideal body weight, avoid stress
and eat regular meals. The average person should not smoke,
eat high fat meals or get an excessive amount of sun
exposure. But how do each of us compare to the average
person in terms of both our behavioral and molecular genetic characteristics?
Thus, despite its vast
potential, genomic medicine remains a “future likelihood” rather than a rapidly
evolving reality, like DNA sequence analysis. Few physicians are capable of
providing interpretation of genomic data to patients. The clinical
relevance of research articles that have not been prepared systematically can
be difficult to assess. Moreover, no current mechanism exists to obtain a
consensus interpretation of the clinical relevance of genomic data using a
standardized format. It is clear that the small number of healthcare
professionals trained in genomics are being overwhelmed by the large number and
complexity of interpretation of new data emerging from genomics research.
The Physician Genome
Partnership was founded on the belief that human genomics will only be able to
revolutionize health care when physicians can interpret genomic data and
incorporate it into their clinical practice. The Partnership has therefore
been established to evaluate all available data in an attempt to provide
systematic assessments of the potential clinical implications of the
data. A secondary goal is to highlight additional data that would further
increase the value of the genomic data. The ultimate goal is to translate
the advances being made in the laboratory to the improvement of health
management in the 21st century.