Clinical Bioinformatics: a Merging of Domains

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Clinical Bioinformatics: a Merging of Domains Clinical applications Clinical bioinformatics: A merging of domains E. Z. Silfen Senior Director, Biomedical Informatics Research, Philips Research North America. This article describes the emergence of the hybrid informatics include: bioinformatics [6], imaging discipline of clinical bioinformatics. Specifically, informatics [7], clinical informatics [8], and it defines biomedical informatics as well as the public health informatics [9]. In addition, sub- four compositional domains of bioinformatics, domains include nursing informatics, consumer imaging informatics, clinical informatics and health informatics, dental informatics, clinical public health informatics. Furthermore, it research informatics, and pharmacy informatics describes the relationship between bioinformatics, [5]. Based upon these academic foundations, E Clinical bioinformatics is a molecular medicine and clinical decision support, this article describes the discipline of clinical hybrid discipline merging and offers a definition of clinical bioinformatics bioinformatics as used by Philips Research in the several domains. that arises from the integration of these domains. pursuit of best patient care. After establishing this background, the article discusses use cases for clinical bioinformatics, Bioinformatics and computational summarizes the field of clinical bioinformatics, biology and posits its potential for biomedicine research. Bioinformatics is the study of biomedicine Biomedical informatics information at the cellular level. The field emphasizes the computational representation, Since the publication in 1959 of Ledley and analysis and presentation of biological information Lusted’s classic article, “Reasoning Foundations at the genomic, epigenomic, transcriptomic, of Medical Diagnosis”[1] the scientific field of proteomic and metabolomic levels [10]. Both biomedical informatics has been evolving as a bioinformatics and computational biology use unique discipline that “studies the structure and methods associated with applied mathematics, properties of scientific information and the laws informatics, statistics, computer science, of all processes of scientific communication” artificial intelligence, chemistry and biochemistry [2]. After evolving over many years, Edward (Ted) to solve biological problems usually on the Shortliffe, MD, PhD, the former chair of the molecular level. Research efforts in computational Department of Biomedical Informatics at biology often overlap with systems biology and Columbia University and recent recipient of the include sequence alignment, gene finding, ACMI Morris F. Collen Award for Excellence in genome assembly, protein structure alignment, the Field of Biomedical Informatics [3], defined protein structure prediction, prediction of gene biomedical informatics as the representation, expression and protein-protein interactions, and storage, retrieval, presentation, sharing, and the modeling of evolution [11]. optimal use of biomedical data, information and knowledge for problem solving and clinical The terms bioinformatics and computational E Biomedical informatics decision making that touches on all basic and biology are often used interchangeably. is the intersection of applied fields in biomedical science and is closely However, bioinformatics more properly refers information science, tied to modern information technologies, notably to the creation and advancement of algorithms, medicine and healthcare. in the areas of computing and communication [4]. computational and statistical techniques, and theory to solve formal and practical problems From a use case perspective, biomedical infor- posed by or inspired from the management and matics represents the intersection of information analysis of biological data. Computational science, medicine and health care. The field biology, on the other hand, refers to hypothesis- addresses the resources, devices and methods driven investigation of a specific biological required to optimize the acquisition, storage, problem using computers, carried out with retrieval and use of information in healthcare experimental and simulated data, with the and biomedicine. Furthermore, biomedicine primary goal of discovery and the advancement tools include not only computers but clinical of biological knowledge. A similar distinction guidelines, formal medical terminologies, and is made by National Institutes of Health in their information and communication systems [5]. working definitions of Bioinformatics and 12 MEDICAMUNDI 51/1 2007/06 The four primary domains of biomedical Computational Biology, where it is further emphasized that there is a tight coupling of advanced design, usability testing, and heuristic developments and knowledge between the more evaluation prior to clinical deployment [15]. hypothesis-driven research in computational The hallmarks of CDSS include: biology and technique-driven research in • The design, development and validation of bioinformatics. Computational biology also the right databases and “intelligent” includes lesser known but equally important algorithms that can ask the right questions to sub-disciplines such as computational mine the data [16]; biochemistry and computational biophysics [12]. • The integration of multiple streams of medical evidence in order to create a clinical Molecular medicine environment that fosters personalized, predictive and pre-emptive medicine; Evolving from computational biology, molecular • Performing evaluation and comparative E Molecular medicine is medicine is the application of the biological effectiveness studies that benchmark the application of the characteristics of disease in order to offer patients applications against ground truth and clinical biological characteristics individualized medical care. By combining domain expertise. of disease. systems biology and informatics methods, molecular medicine creates an ‘omics’ medicine For patients, expert decision systems are essential approach [13] that identifies and internally for improving clinical outcomes, while for validates markers of cellular function for use in clinicians these solutions are necessary for clinically enabling technologies. workflow and care process improvement. In summary, CDSS relies upon computer- Molecular medicine can be sub-divided into supported systems that enable physicians to molecular diagnostics and molecular imaging. optimally use biomedical data, information and Based on the in vitro detection of biomarkers, knowledge for problem solving and clinical molecular diagnostics focuses on testing for decision making [17]. specific molecules associated with disease in order to determine an individual patient’s Clinical bioinformatics predisposition to illness, screen patients for the presence of a medical condition, plan personalized Clinical bioinformatics emerges from the therapeutic approaches, and monitor the intersection of the methods, techniques, patient’s response to therapeutic interventions. applications, and solutions of bioinformatics, molecular medicine and clinical decision As a companion modality, molecular imaging support. This “overlap” enables integration of emphasizes the identification of the in vivo evidence, thereby affording physicians more location and extent of disease by gauging the robust medical decision making capability [18] presence of specific molecules associated with a (Figure 1). disease. The core technology requires medical imaging equipment that can detect and quantify Specifically, as clinical decision support systems disease-specific, molecular contrast agents. blend biomarker information into the expert When combined with molecular diagnostic systems necessary for evidence-based patient methods, molecular imaging can offer important care, significant opportunities arise for clinical information for both the planning and bioinformatics research [19]. Two of these are monitoring phases of medical therapy. the use of previously identified genetic E Molecular medicine information for making medical care decisions, demands reliable and The sine qua non for molecular medicine is the and the simulation of disease processes to guide accurate identification reliable and accurate identification and the “type and timing” of therapeutic of the molecular pattern measurement of an individual’s biomolecular interventions. Examples of genetic applications of disease. pattern of disease as well as their treatment include: response profile [14]. This characterization • Clinical correlation of genetic information. enables the integration of the final component That is, genetic diseases might be caused by necessary for defining the discipline of clinical different mutations of a single gene or by bioinformatics, clinical decision support. mutations of different genes that are related, for example, because they code for different Clinical decision support systems enzymes in a single metabolic pathway [20, 21, 22]. Clinical Decision Support Systems (CDSS) is • Genetic variation may be correlated with the branch of biomedical informatics that different levels of severity of a disease or different unifies knowledge discovery with engineering presentations of signs or symptoms [23]. techniques to create expert systems. • Patients with different genetic makeup may These systems require clinical evaluation, have different responses to treatment. The new MEDICAMUNDI 51/1 2007/06 13 E 1 Figure 1: Clinical Bioinformatics as a merger of the classical domains of bioinformatics, molecular medicine and clinical decision support.
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