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Summary
The Committee’s charge was to explore the feasibility and need for “a
New Taxonomy of human disease based on molecular biology” and to develop
a potential framework for creating one. Clearly, the motivation for this study
is the explosion of molecular data on humans, particularly those associated
with individual patients, and the sense that there are large, as-yet-untapped
opportunities to use these data to improve health outcomes. The Committee
agreed with this perspective and, indeed, came to see the challenge of develop -
ing a New Taxonomy of Disease as just one element, albeit an important one,
in a truly historic set of health-related challenges and opportunities associated
with the rise of data-intensive biology and rapidly expanding knowledge of the
mechanisms of fundamental biological processes. Hence, many of the implica -
tions of the Committee’s findings and recommendations ramify far beyond the
science of disease classification and have substantial implications for nearly all
stakeholders in the vast enterprise of biomedical research and patient care.
Given the scope of the Committee’s deliberations, it is appropriate to start
this report by tracing the logical thread that unifies the Committee’s major
findings and recommendations and connects them to its statement of task. The
Committee’s charge highlights the importance of taxonomy in medicine and
the potential opportunities to use molecular data to improve disease taxonomy
and, thereby, health outcomes. Taxonomy is the practice and science of clas -
sification, typically considered in the context of biology (e.g., the Linnaean
system for classifying living organisms). In medical practice, taxonomy often
refers to the International Classification of Diseases (ICD), a system established
more than 100 years ago that the World Health Organization uses to track
disease incidence, physicians use as a basis for standardized diagnoses, and
the health-care industry (specifically, clinicians, hospitals, and payers) uses to
1
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2 TOWARD PRECISION MEDICINE
determine reimbursement for care. Although the Committee was cognizant that
any new-taxonomy initiative must serve the needs of the ICD and related clas -
sification systems, it concluded that this goal could best be met by rooting fu-
ture improvements in disease classification in an “Information Commons” and
“Knowledge Network” that would play many other roles, as well. The Com -
mittee envisions these data repositories as essential infrastructure, necessary
both for creating the New Taxonomy and, more broadly, for integrating basic
biological knowledge with medical histories and health outcomes of individual
patients. The Committee believes that building this infrastructure—the Infor-
mation Commons and Knowledge Network—is a grand challenge that, if met,
would both modernize the ways in which biomedical research is conducted and,
over time, lead to dramatically improved patient care (see Figure S-1).
The Committee envisions this ambitious program, which would play out
on a time scale of decades rather than years, as proceeding through a blend of
top-down and bottom-up activity. A major top-down component, initiated by
public and private agencies that fund and regulate biomedical research, would
be required to ensure that results of individual projects could be combined to
FIGURE S-1 Creation of a New Taxonomy first requires an “Information Commons”
in which data on large populations of patients become broadly available for research
use and a “Knowledge Network” that adds value to these data by highlighting their
Figure S-1, 1-3
inter-connectedness and integrating them with evolving knowledge of fundamental
Bitmapped
biological processes.
SOURCE: Committee on A Framework for Developing a New Taxonomy of Disease.
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3
SUMMARY
create a broadly useful and accessible Information Commons and to establish
guidelines for handling the innumerable social, ethical, and legal issues that will
arise as data on individual patients become widely shared research resources.
However, as is appropriate for a framework study, the Committee did not at -
tempt to design the Information Commons, the Knowledge Network, or the
New Taxonomy itself and would discourage funding agencies from over-speci -
fying these entities in advance of initial efforts to create them. What is needed,
in the Committee’s view, is a creative period of bottom-up research activity,
organized through pilot projects of increasing scope and scale, from which the
Committee is confident best practices would emerge. Particularly given the size
and diversity of the health-care enterprise, no one approach to gathering the
data that will populate the Information Commons is likely to be appropriate
for all contributors. As in any initiative of this complexity, what will be needed
is the right level of coordination and encouragement of the many players who
will need to cooperate to create the Information Commons and Knowledge
Network and thereby develop a New Taxonomy. If coordination is too rigid,
much-needed innovation and adaptation to local circumstances will be stifled,
while if it is too lax, it will be impossible to integrate the data that are gathered
into a whole whose value greatly exceeds that of the sum of its parts, an objec -
tive the Committee believes is achievable with effective central leadership.
CONCLUSIONS
The Committee hosted a two-day workshop that convened diverse experts
in both basic and clinical disease biology to address the feasibility, need, scope,
impact, and consequences of creating a “New Taxonomy of human diseases
based on molecular biology”. The information and opinions conveyed at the
workshop informed and influenced an intensive series of Committee delibera -
tions (in person and by teleconference) over a six-month period, which led to
the following conclusions:
A New Taxonomy will lead to better health care. Because new infor-
1.
mation and concepts from biomedical research cannot be optimally
incorporated into the disease taxonomy of today, opportunities to
define diseases more precisely and to inform health-care decisions are
being missed. Many disease subtypes with distinct molecular causes
are still classified as one disease and, conversely, multiple different
diseases share a common molecular cause. The failure to incorporate
optimally new biological insights results in delayed adoption of new
practice guidelines and wasteful health-care expenditures for treat -
ments that are only effective in specific subgroups.
The time is right to modernize disease taxonomy. Dramatic ad-
2.
vances in molecular biology have enabled rapid, comprehensive and
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cost-efficient analysis of clinical samples, resulting in an explosion of
disease-relevant data with the potential to dramatically alter disease
classification. Fundamental discovery research is defining at the molec-
ular level the processes that define and drive physiology. These devel-
opments, coupled with parallel advances in information technologies
and electronic medical records, provide a transformative opportunity
to create a new system to classify disease.
A New Taxonomy should be developed. A New Taxonomy that inte-
3.
grates multi-parameter molecular data with clinical data, environmen -
tal data, and health outcomes in a dynamic, iterative fashion, is feasible
and should be developed. The Committee envisions a comprehensive
disease taxonomy that brings the biomedical-research, public health,
and health-care-delivery communities together around the related
goals of advancing our understanding of disease pathogenesis and
improving health. Such a New Taxonomy would
• escribe and define diseases based on their intrinsic biology in
D
addition to traditional physical “signs and symptoms.”
• o beyond description and be directly linked to a deeper under-
G
standing of disease mechanisms, pathogenesis, and treatments.
• e highly dynamic, at least when used as a research tool, continu-
B
ously incorporating newly emerging disease information.
A Knowledge Network of Disease would Enable a New Taxonomy.
4.
The informational infrastructure required to create a New Taxonomy
with the characteristics described above overlaps with that required to
modernize many other facets of biomedical research and patient care.
This infrastructure requires an “Information Commons” in which data
on large populations of patients become broadly available for research
use and a “Knowledge Network” that adds value to these data by high-
lighting their inter-connectedness and integrating them with evolving
knowledge of fundamental biological processes.
New models for population-based research will enable development
5.
of the Knowledge Network and New Taxonomy. Current population-
based studies of disease are relatively inefficient and can generate
conclusions that are not relevant to broader populations. Widespread
incorporation of electronic medical records into the health-care system
will make it possible to conduct such research at “point-of-care” in
conjunction with the routine delivery of medical services. Moreover,
only if the linked phenotypic data is acquired in the ordinary course
of clinical care is it likely to be economically feasible to characterize a
sufficient number of patients and ultimately to create a self-sustaining
system (i.e., one in which the costs of gathering molecular data on
individual patients can be medically justified in cost-benefit terms).
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SUMMARY
Redirection of resources could facilitate development of the
6.
Knowledge Network of Disease. The initiative to develop a New
Taxonomy—and its underlying Information Commons and Knowl-
edge Network—is a needed modernization of current approaches to
integrating molecular, environmental, and phenotypic data, not an
“add-on” to existing research programs. Enormous efforts are already
underway to achieve many of the goals of this report. In the Com -
mittee’s view, what is missing is a system-wide emphasis on shifting
the large-scale acquisition of molecular data to point-of-care settings
and the coordination required to ensure that the products of the re-
search will coalesce into an Information Commons and Knowledge
Network from which a New Taxonomy (and many other benefits)
can be derived. In view of this conclusion, the Committee makes no
recommendations about the resource requirements of the New Tax-
onomy initiative. Obviously, the process could be accelerated with new
resources; however, the basic thrust of the Committee’s recommenda -
tions could be pursued by redirection of resources already dedicated
to increasing the medical utility of large-scale molecular datasets on
individual patients.
RECOMMENDATIONS
To create a New Taxonomy and its underlying Information Commons and
Knowledge Network, the Committee recommends the following:
Conduct pilot studies that begin to populate the Information Com-
1.
mons with data. Pilot observational studies should be conducted in
the health-care setting to assess the feasibility of integrating molecular
parameters with medical histories and health outcomes in the ordinary
course of clinical care. These studies would address the practical and
ethical challenges involved in creating, linking, and making broadly
accessible the datasets that would underlie the New Taxonomy. Best
practices defined by the pilot studies should then be expanded in
scope and scale to produce an Information Commons and Knowledge
Network that are adequately powered to support a New Taxonomy.
As this process evolves, there should be ongoing assessment of the
extent to which these new informational resources actually contribute
to improved health outcomes and to more cost-effective delivery of
health care.
Integrate Data to Construct a Disease Knowledge Network. As data
2.
from point-of-care pilot studies, linked to individual patients, begin to
populate the Information Commons, substantial effort should go into
integrating these data with the results of basic biomedical research
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in order to create a dynamic, interactive Knowledge Network. This
network, and the Information Commons itself, should leverage state-
of-the-art information technology to provide multiple views of the
data, as appropriate to the varying needs of different users (e.g., basic
researchers, clinicians, outcomes researchers, payers).
Initiate a process within an appropriate federal agency to assess
3.
the privacy issues associated with the research required to create
the Information Commons. Because these issues have been studied
extensively, this process need not start from scratch. However, in
practical terms, investigators who wish to participate in the pilot stud -
ies discussed above—and the Institutional Review Boards who must
approve their human-subjects protocols—will need specific guidance
on the range of informed-consent processes appropriate for these proj-
ects. Subject to the constraints of current law and prevailing ethical
standards, the Committee encourages as much flexibility as possible
in the guidance provided. As much as possible, on-the-ground experi -
ence in pilot projects carried out in diverse health-care settings, rather
than top-down dictates, should govern the emergence of best practices
in this sensitive area, whose handling will have a make-or-break influ -
ence on the entire Information Commons/Knowledge Network/New
Taxonomy initiative. Inclusion in these deliberations of health-care
providers, payers, and other stakeholders outside the academic com-
munity will be essential.
Ensure data sharing. Widespread data sharing is critical to the success
4.
of each stage of the process by which the Committee envisions creating
a New Taxonomy. Most fundamentally, the molecular and phenotypic
data on individual patients that populate the Information Commons
must be broadly accessible so that a wide diversity of researchers
can mine them for specific purposes and explore alternate ways of
deriving Knowledge Networks and disease taxonomies from them.
Current standards developed and adopted by federally sponsored
genome projects have addressed some of these issues, but substantial
barriers, particularly to the sharing of phenotypic and health-outcomes
data on individual patients, remain. Data-sharing standards should
be created that respect individual privacy concerns while enhancing
the deposition of data into the Information Commons. Importantly,
these standards should provide incentives that motivate data sharing
over the establishment of proprietary databases for commercial intent.
Resolving these impediments may require legislation and perhaps evo-
lution in the public’s expectations with regard to access and privacy of
health-care data.
Develop an efficient validation process to incorporate information
5.
from the Knowledge Network of Disease into a New Taxonomy.
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SUMMARY
Insights into disease classification that emerge from the Information
Commons and the derived Knowledge Network will require validation
of their reproducibility and their utility for making clinically relevant
distinctions (e.g., regarding prognosis or choice of treatment) before
adoption into clinical use. A process should be established by which
such information is validated for incorporation into a New Taxonomy
to be used by physicians, patients, regulators, and payers. The speed
and complexity with which such validated information emerges will
undoubtedly accelerate and will require novel decision-support sys -
tems for use by all stakeholders.
Incentivize partnerships. The Committee envisions that a New Tax-
6.
onomy incorporating molecular data could become self-sustaining by
accelerating delivery of better health through more accurate diagnosis
and more effective and cost-efficient treatments. However, to cover
initial costs associated with collecting and integrating data for the In -
formation Commons, incentives should be developed that encourage
public–private partnerships involving government, drug developers,
regulators, advocacy groups, and payers.
A major beneficiary of the proposed Knowledge Network of Disease and
New Taxonomy would be what has been termed “precision medicine.” The
Committee is of the opinion that realizing the full promise of precision medi -
cine, whose goal is to provide the best available care for each individual,
requires that researchers and health-care providers have access to vary large
sets of health and disease-related data linked to individual patients. These
data are also critical for the development of the Information Commons, the
Knowledge Network of Disease, and the development and validation of the
New Taxonomy.
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