testing to assess their individual breast cancer predisposition (Siemens Healthcare Diagnostics Inc. 2008).
In contrast, Patient 2 has been diagnosed at age 40 with type 2 diabetes, an imprecise category that serves primarily to distinguish his disease from diabetes that typically occurs at younger ages (type 1) or during pregnancy (gestational). The diagnosis gives little insight into the specific molecular pathophysiology of the disease and its complications; similarly there is little basis for tailoring treatment to a patient’s pathophysiology. The patient’s internist will likely prescribe metformin, a drug used for over 50 years and still the most common treatment for type II diabetes in the United States. No concrete molecular information is available to customize Patient 2’s therapy to reduce his risk for kidney failure, blindness or other diabetes-related complications. No tests are available to measure risk of diabetes for his siblings and children. Patient 2 and his family are not yet benefitting from today’s explosion of information on the pathophysiology of disease (A.D.A.M. Medical Encyclopedia 2011; Gordon 2011; Kellett 2011).
What elements of our research and medical enterprise contribute to making the Patient 1 scenario exceptional, and Patient 2 typical? Could it be that something as fundamental as our current system for classifying diseases is actually inhibiting progress? Today’s classification system is based largely on measurable “signs and symptoms,” such as a breast mass or elevated blood sugar, together with descriptions of tissues or cells, and often fail to specify molecular pathways that drive disease or represent targets of treatment.2 Consider a world where a diagnosis itself routinely provides insight into a specific pathogenic pathway. Consider a world where clinical information, including molecular features, becomes part of a vast “Knowledge Network of Disease” that would support precise diagnosis and individualized treatment. What if the potential of molecular features shared by seemingly disparate diseases to suggest radically new treatment regimens were fully realized? In such a world, a new, more accurate and precise “taxonomy of disease” could enable each patient to benefit from and contribute to what is known.
In consideration of such possibilities, and at the request of the Director of the National Institutes of Health, an ad hoc Committee of the National Research Council was convened to explore the feasibility and need, and to develop a potential framework, for creating “a New Taxonomy of human diseases based on molecular biology” (Box 1-1). The Committee hosted a two- day workshop
2 To clarify, the committee is not suggesting that all diseases would have an equally precise taxonomy, rather each disease should be classified, and treatment provided, using the best available molecular information about the mechanism of disease.