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Biomedical Informatics and Translational Medicine Indra Neil Sarkar Sarkar Journal of Translational Medicine 2010, 8:22 http://www.translational-medicine.com/content/8/1/22 REVIEW Open Access Biomedical informatics and translational medicine Indra Neil Sarkar Abstract Biomedical informatics involves a core set of methodologies that can provide a foundation for crossing the “trans- lational barriers” associated with translational medicine. To this end, the fundamental aspects of biomedical infor- matics (e.g., bioinformatics, imaging informatics, clinical informatics, and public health informatics) may be essential in helping improve the ability to bring basic research findings to the bedside, evaluate the efficacy of interventions across communities, and enable the assessment of the eventual impact of translational medicine innovations on health policies. Here, a brief description is provided for a selection of key biomedical informatics topics (Decision Support, Natural Language Processing, Standards, Information Retrieval, and Electronic Health Records) and their relevance to translational medicine. Based on contributions and advancements in each of these topic areas, the article proposes that biomedical informatics practitioners ("biomedical informaticians”) can be essential members of translational medicine teams. Introduction interventions might be worthy to consider[12]. Next, Biomedical informatics, by definition[1-8], incorporates directed evaluations (e.g., randomized controlled trials) a core set of methodologies that are applicable for are used to identify the efficacy of the intervention and managing data, information, and knowledge across the to provide further insights into why aproposedinter- translational medicine continuum, from bench biology vention works[12]. Finally, the ultimate success of an to clinical care and research to public health. To this intervention is the identification of how it can be appro- end, biomedical informatics encompasses a wide range priately scaled and applied to an entire population[12]. of domain specific methodologies. In the present dis- The various contexts presented across the translational course, the specific aspects of biomedical informatics medicine spectrum enable a “grounding” of biomedical that are of direct relevance to translational medicine are: informatics approaches by providing specific scenarios (1) bioinformatics; (2) imaging informatics; (3) clinical where knowledge management and integration informatics; and, (4) public health informatics. These approaches are needed. Between each of these steps, support the transfer and integration of knowledge across translational barriers are comprised of the challenges the major realms of translational medicine, from mole- associated with the translation of innovations developed cules to populations. A partnership between biomedical through bench-based experiments to their clinical vali- informatics and translational medicine promises the bet- dation in bedside clinical trials, ultimately leading to terment of patient care[9,10] through development of their adoption by communities and potentially leading new and better understood interventions used effectively to the establishment of policies. The crossing of each in clinics as well as development of more informed poli- translational barrier ("T1,”“T2,” and “T3,” respectively cies and clinical guidelines. corresponding to translational barriers at the bench-to- The ultimate goal of translational medicine is the bedside, bedside-to-community, and community-to-pol- development of new treatments and insights towards icy interfaces; as shown in Figure 1) may be greatly the improvement of health across populations[11]. The enabled through the use of a combination of existing first step in this process is the identification of what and emerging biomedical informatics approaches[9]. It is particularly important to emphasize that, while the major thrust is in the forward direction, accomplish- [email protected] Center for Clinical and Translational Science, Department of Microbiology ments, and setbacks can be used to valuably inform and Molecular Genetics, & Department of Computer Science, University of both sides of each translational barrier (as depicted by Vermont, College of Medicine, 89 Beaumont Ave, Given Courtyard N309, the arrows in Figure 1). An important enabling step to Burlington, VT 05405 USA © 2010 Sarkar; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Sarkar Journal of Translational Medicine 2010, 8:22 Page 2 of 12 http://www.translational-medicine.com/content/8/1/22 Figure 1 The synergistic relationship across the biomedical informatics and translational medicine continua. Major areas of translational medicine (along the top; innovation, validation, and adoption) are depicted relative to core focus areas of biomedical informatics (along the bottom; molecules and cells, tissues and organs, individuals, and populations). The crossing of translational barriers (T1, T2, and T3) can be enabled using translational bioinformatics and clinical research informatics approaches, which are comprised of methodologies from across the sub-disciplines of biomedical informatics (e.g., bioinformatics, imaging informatics, clinical informatics, and public health informatics). cross the translational barriers is the development of still tenable in the context of translational medicine. trans-disciplinary teams that are able to integrate rele- Much of the identified synergy between biomedical vant findings towards the identification of potential informatics and translational medicine can be organized breakthroughs in research and clinical intervention[13]. into two major categories that build upon the sub-disci- To this end, biomedical informatics professionals ("bio- plines of biomedical informatics (as shown in Figure 1): medical informaticians”) may be an essential addition to (1) translational bioinformatics (which primarily consists a translational medicine team to enable effective transla- of biomedical informatics methodologies aimed at cross- tion of concepts between team members with heteroge- ing the T1 translational barrier) and (2) clinical research neous areas of expertise. informatics (which predominantly consists of biomedical Translational medicine teams will need to address informatics techniques from the T1 translational barrier many of the challenges that have been the focus of bio- across the T2 and T3 barriers). It is important to medical informatics since the inception of the field. emphasize that the role of biomedical informatics in the What follows is a brief description of biomedical infor- context of translational medicine is not to necessarily matics, followed by a discussion of selected key topics create “new” informatics techniques[16]. Instead, it is to that are of relevance for translational medicine: (1) Deci- apply and advance the rich cadre of biomedical infor- sion Support; (2) Natural Language Processing; (3) Stan- matics approaches within the context of the fundamen- dards; (4) Information Retrieval; and, (5) Electronic tal goal of translational medicine: facilitate the Health Records. For each topic, progress and activities application of basic research discoveries towards the bet- in bio-, imaging, clinical and public health informatics terment of human health or treatment of disease[17]. are described. The article then concludes with a consid- Clinical informatics has historically been described as a eration of the role of biomedical informaticians in trans- field that meets two related, but distinct needs[18]: lational medicine teams. patient-centric and knowledge-centric. This notion can be generalized for all of biomedical informatics within the Biomedical Informatics context of translational medicine to suggest that the goals Biomedical informatics is an over-arching discipline that are either to meet the needs of user-centric stakeholders includes sub-disciplines such as bioinformatics, imaging (e.g., biologists, clinicians, epidemiologists, and health ser- informatics, clinical informatics, and public health infor- vices researchers) or knowledge-centric stakeholders (e.g., matics; the relationships between the sub-disciplines researchers or practitioners at the bench, bedside, com- have been previously well characterized[7,14,15], and are munity, and population level). Bioinformatics approaches Sarkar Journal of Translational Medicine 2010, 8:22 Page 3 of 12 http://www.translational-medicine.com/content/8/1/22 are needed to identify molecular and cellular regions that necessary communication and translation of concepts can be targeted with specific clinical interventions or between members of trans-disciplinary translational studied to provide better insights to the molecular and medicine teams. cellular basis of disease[19-25]. Imaging informatics tech- niques are needed for the development and analysis of Decision Support visualization approaches for understanding pathogenesis Decision support systems are information management and identification of putative treatments from the mole- systems that facilitate the making of decisions by biome- cular, cellular, tissue or organ level[26-29]. Clinical infor- dical stakeholders through the intelligent filtering of matics innovations are needed to improve patient care possible decisions based on a
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