“Facilitating Clinical and Translational Research Using Biomedical Informatics”
The vast majority of human diseases are the product of multi-step processes that involve the complex
interplay of a multitude of genes acting at different levels of the genetic program. These genes are
integrated and manifested as systemic phenotypes or medical findings detected during routine patient
care or as part of clinical research studies. This fundamental observation has underscored the need to
integrate basic science and clinical medicine more tightly, thus facilitating the rise of translational
research as a distinct field in biomedicine. The goal of this field is to rapidly convert novel advances in
basic science to improvements in patient care and to relay findings from clinical studies employing such
new, and increasingly customized diagnostics and therapeutics back to the bench for further refinement
of our understanding of the disease process. However, two significant roadblocks have been identified
that make this translation difficult. The first translational roadblock (T1) is in the conversion of bench
science findings to the development of tests for diagnosis, prognosis, or prevention or of customized
therapies that may then be tested in humans. In contrast, the second translational block (T2) is in the
transformation of results from clinical research studies to broadly accepted and implemented health care
practices. While the former is focused more on the bench sciences and clinical research, the latter is
focused on population-based studies. While addressing each of the translational blocks requires mastery
of largely non-overlapping research disciplines (e.g. T1 requires the biological and clinical sciences, and
T2 requires clinical epidemiology, behavioral science, public policy, communication theory, and qualitative
research), the application and advancement of the inter-disciplinary field of biomedical informatics
(BMI) is crucial for tackling both T1 and T2. BMI combines the quantitative disciplines of information and
computer sciences and statistics with social sciences such as psychology and communication theory and
the research and healthcare domains of bench science and clinical research, clinical medicine, and public
health. Current translational blocks pertinent to informatics exist both within and between research,
clinical, and government organizations such as academic institutions, intramural government research
initiatives, inter-institutional clinical or research cooperatives, pharmaceutical companies, and healthcare
providers. Namely, efficient knowledge transfer and access within and amongst these entities are
severely hampered by the following:
1) Inability of informatics applications to syntactically interoperate (i.e. are ‘silos’ of data), forcing the
end user to manage and transform data between tools.
2) Ineffective use of controlled vocabularies and standards-based, reusable common data elements
that promote data integration and semantic interoperability of diverse population, clinical,
biospecimen, imaging, and research data sets.
3) Lack of tools to facilitate data acquisition and storage using industry standard software design
principles.
4) Unavailability of statistically sound software applications to co-analyze and visualize complex
population and biomedical data sets (T1) or mathematically robust decision support tools (T2)
using appropriate security measures and employing user-friendly interfaces that facilitate basic
and advanced physician, clinician-scientist, or bench researcher workflows and processes.
In this presentation, both local and nationwide/global solutions to address these roadblocks will be
presented.