Press
Room
Key Factors Influencing
the Adoption Genomics in the Clinic:
Ginsburg of Millennium Pharmaceuticals
The
link to this article is on the CHI website:
http://www.healthtech.com/newsarticles/issue43_1.asp
The clinical genomics environment is
ripe with opportunities for all players in the field—pharmaceutical
companies, biotech firms, diagnostics manufacturers, tool
suppliers, and researchers—as the NIH and FDA make
it clear that increased use of genomics in the practice
of medicine and drug development is both anticipated and
encouraged. However, clinical genomics is far from widespread
and still faces significant hurdles. In this article, Geoffrey
S. Ginsburg, MD, PhD, Vice President, Molecular Medicine
at Millennium Pharmaceuticals, Inc., discusses some of
the most important factors that will influence the adoption
of genomics technologies in clinical trials and medical
practice. This commentary was excerpted from the new Cambridge
Healthtech report, Clinical Genomics: The Impact
of Genomic Technology on Clinical Trials and Medical Practice.
For more information about this report, please visit http://www.advancesreports.com/all_reports/.
The Molecular Medicine group at Millennium
has the goal to develop biomarkers that inform our early-stage
clinical genomic programs, and also to employ pharmacogenomics
for risk-stratifying genetic strategies in our late-stage development
programs so that we can optimize the efficacy of compounds
in our pipeline. A theme at Millennium is that genomics is
really integral to everything we do. I do not think there is
a program in drug discovery and development at Millennium that
does not utilize genomic technologies developed within the
last ten years.
We have tried to weave the concept of using
genetics and genomics throughout clinical development as an
important differentiating strategy for us. And I think that
because of our size and our flexibility, we have actually been
able to do this organizationally; we have made a commitment
to create a "biomarker working group" for every molecule
in our pipeline, a group that is responsible for guiding the
molecule’s biomarker strategy as well as the potential
commercialization strategy. I certainly believe that other
pharmaceutical companies are evaluating and implementing molecular
medicine strategies, but I would also like to believe that
we are on the leading edge in this area.
Today, we are seeing only the tip of the
iceberg of the full potential of clinical genomics. I believe
over the next decade, we are going to see a tsunami of genetic
information entering the clinical arena. This information will
come not only from the pharmaceutical companies, but also from
academic laboratories that are willing and committed to understanding
the molecular underpinnings of disease.
As the technology becomes more validated
and reproducible, it will become more standardized, and I think
it will become increasingly incorporated into clinical decision-making.
Another factor driving genomics into clinical decision-making
is that the timeline for developing predictive tests based
on genomics, in my mind, is much shorter than the timelines
for developing a drug, because of the prerequisites for Phase
I, II, and III studies in drug development.
However, there are a number of hurdles for
further adoption of genomic technologies in clinical settings.
The first one I will broadly categorize as education. Clinicians
are not well trained in the application of genomics and genomic
technology—from medical school, to fellowship, and through
graduate education there needs to be a focus on these applications.
I think that the medical community in general needs to get
caught up on the implications of genomics for patient care.
I believe that medical professional organizations need to take
a much more active role in educating physicians about genomics
and how it is going to be implemented into medical practice.
Secondly, because physicians are incredibly
constrained in terms of time and information synthesis, there
has got to be a way to deliver information about the genomics
and its clinical utility for decision making in a way that
is going to be pragmatic in practice. Finally, there are challenges
in other areas of implementation. There are technological—how
will these platforms be used in the day-to-day practice of
medicine in a facile way? In addition, patients are going to
be inundated with large volumes of information, and who will
make sure they are adequately prepared? There are public policy
issues around privacy, intellectual property, and also who
will pay for the additional tests? Today diagnostic tests may
increase health care costs initially, but hopefully the benefits
will be achieved later on. But a big question still remains
as to whether third-party payers will support and encourage
adoption of this technology.
One of the things that should be kept in
mind about personalized medicine strategies is that at the
end of the day, it is going to actually make drugs less expensive
to develop, but it requires a technology investment in order
to get there. So, we should set expectations properly. The
IT infrastructure, the challenges of data analysis, or even
increasing the accuracy of technology, is going to require
an investment up front until it is more robust, effective,
and standardized. We should make clear that it is going to
cost more in the short run to achieve some of the long-term
benefits of this paradigm, such as reducing failure rates in
clinical development and reducing the timelines and numbers
of patients required for clinical trials. These are all, I
think, very achievable goals in the long run.
I tend to view pharmaceutical companies and
bio-pharmaceutical companies as trying to understand the behavior
of the drug in the context of a specific disease, and thus
are limited in scope to the drug more than the disease. It
is academia that is best positioned to better understand diseases
and their molecular sub-classification—after all, that
is in line with the mission of the academy and that is where
the patients are.
There is a new paradigm evolving for how
we actually do translational research that brings together
groups that have not previously worked together. Academic medical
centers have the patients, and they have individuals with specialized
knowledge about the disease. Industry brings to the relationship
important molecular tools that can be used to integrate pathways,
and also large technology platforms that are designed and integrated
in ways that is probably not the case in many academic centers.
Imaging companies can contribute technology to measure disease
and effects of drugs on disease. IT companies can help build
the infrastructure. Finally, government can help create and
implement guidelines to facilitate the process. This is certainly
commensurate with what the NIH is thinking as part of the "roadmap" in
developing regional centers of translational medicine that
are formed by public-private partnerships. In the end, having
a multi-faceted collaboration including industry, with academic
and government participation, is how translational research
in genomic medicine will be accomplished in the future.
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