Translational Research from an Informatics Perspective

Clinical and translational research (CTR) is an essential part of a sustainable global health system. Informatics is now recognized as an important en-abler of CTR and informaticians are increasingly called upon to help CTR efforts. The US National Institutes of Health mandated biomedical informatics activity as part of its new national CTR grant initiative, the Clinical and Translational Science Award (CTSA). Traditionally, translational re-search was defined as the translation of laboratory discoveries to patient care (bench to bedside). We argue, however, that there are many other kinds of translational research. Indeed, translational re-search requires the translation of knowledge dis-covered in one domain to another domain and is therefore an information-based activity. In this panel, we will expand upon this view of translational research and present three different examples of translation to illustrate the point: 1) bench to bedside, 2) Earth to space and 3) academia to community. We will conclude with a discussion of our local translational research efforts that draw on each of the three examples

Creating an Interactive DNP Project Repository:A Model for Change

The creation of systems that can provide bridges to information technology requires rethinking old ways of doing business. In the past, individual universities and colleges would accommodate theses and dissertations on their library sites. Some of these sites are public and can be accessed by everyone, while some require university-specific affiliation. This project aims to apply knowledge and skills related to information systems and technology. With the growth of the DNP clinical doctorate programs, and final outcome projects there is a need for specialized DNP database for a new method of data entry and retrieval for DNP’s. The creation of a resource specific to DNP students and faculty can provide easier access to evidence-based projects. Specialization of this database to help track trends and projects of DNP students from different DNP programs and can later be a source for research into the quality and outcomes of DNP final projects across the country. The purpose of this project is to develop consensus as to the valuable aspects related to the creation of a centralized electronically accessible databank for DNP final student projects. The goal is to provide a shortened pathway to get DNP final projects’ evidence-based outcomes easily accessible for people within and outside the DNP program. DNP students in programs across the country could easily access what other students have submitted as final projects, from which they could build on ideas or adapt project criteria to meet the needs of their individual settings

Translational informatics of population health: How large biomolecular and clinical datasets unite

This paper summarizes the workshop content on how the integration of large biomolecular and clinical datasets can enhance the field of population health via translational informatics. Large volumes of data present diverse challenges for existing informatics technology, in terms of computational efficiency, modeling effectiveness, statistical computing, discovery algorithms, and heterogeneous data integration. While accumulating large 'omics measurements on subjects linked with their electronic record remains a challenge, this workshop focuses on non-trivial linkages between large clinical and biomolecular datasets. For example, exposures and clinical datasets can relate through zip codes, while comorbidities and shared molecular mechanisms can relate diseases. Workshop presenters will discuss various methods developed in their respective labs/organizations to overcome the difficulties of combining together such large complex datasets and knowledge to enable the translation to clinical practice for improving health outcomes.Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Facilitating and Enhancing Biomedical Knowledge Translation: An in Silico Approach to Patient-centered Pharmacogenomic Outcomes Research

Current research paradigms such as traditional randomized control trials mostly rely on relatively narrow efficacy data which results in high internal validity and low external validity. Given this fact and the need to address many complex real-world healthcare questions in short periods of time, alternative research designs and approaches should be considered in translational research. In silico modeling studies, along with longitudinal observational studies, are considered as appropriate feasible means to address the slow pace of translational research. Taking into consideration this fact, there is a need for an approach that tests newly discovered genetic tests, via an in silico enhanced translational research model (iS-TR) to conduct patient-centered outcomes research and comparative effectiveness research studies (PCOR CER). In this dissertation, it was hypothesized that retrospective EMR analysis and subsequent mathematical modeling and simulation prediction could facilitate and accelerate the process of generating and translating pharmacogenomic knowledge on comparative effectiveness of anticoagulation treatment plan(s) tailored to well defined target populations which eventually results in a decrease in overall adverse risk and improve individual and population outcomes. To test this hypothesis, a simulation modeling framework (iS-TR) was proposed which takes advantage of the value of longitudinal electronic medical records (EMRs) to provide an effective approach to translate pharmacogenomic anticoagulation knowledge and conduct PCOR CER studies. The accuracy of the model was demonstrated by reproducing the outcomes of two major randomized clinical trials for individualizing warfarin dosing. A substantial, hospital healthcare use case that demonstrates the value of iS-TR when addressing real world anticoagulation PCOR CER challenges was also presented

Translational Medicine and Patient Safety in Europe:TRANSFoRm - Architecture for the Learning Health System in Europe

The Learning Health System (LHS) describes linking routine healthcare systems directly with both research translation and knowledge translation as an extension of the evidence-based medicine paradigm, taking advantage of the ubiquitous use of electronic health record (EHR) systems. TRANSFoRm is an EU FP7 project that seeks to develop an infrastructure for the LHS in European primary care. Methods. The project is based on three clinical use cases, a genotype-phenotype study in diabetes, a randomised controlled trial with gastroesophageal reflux disease, and a diagnostic decision support system for chest pain, abdominal pain, and shortness of breath. Results. Four models were developed (clinical research, clinical data, provenance, and diagnosis) that form the basis of the projects approach to interoperability. These models are maintained as ontologies with binding of terms to define precise data elements. CDISC ODM and SDM standards are extended using an archetype approach to enable a two-level model of individual data elements, representing both research content and clinical content. Separate configurations of the TRANSFoRm tools serve each use case. Conclusions. The project has been successful in using ontologies and archetypes to develop a highly flexible solution to the problem of heterogeneity of data sources presented by the LHS

Biomedical informatics and translational medicine

Biomedical informatics involves a core set of methodologies that can provide a foundation for crossing the "translational barriers" associated with translational medicine. To this end, the fundamental aspects of biomedical informatics (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

Ontological Meta-Analysis and Synthesis

We present ontological meta-analysis and synthesis as a method for reviewing, mapping, and visualizing the research literature in a domain cumulatively, logically, systematically, and systemically. The method will highlight the domain’s bright spots which are heavily emphasized, the light spots which are lightly emphasized, the blank spots which are not emphasized, and the blind spots which have been overlooked. It will highlight the biases and asymmetries in the domain’s research; the research can then be realigned to make it stronger and more effective. We illustrate the method using the emerging domain of Public Health Informatics (PHI). We present an ontological framework for the domain, map the literature onto the framework, and highlight its bright, light, and blank/blind spots. We conclude with a discussion of how (a) the results can be used to realign PHI research, and (b) the method can be used in other information systems domains

Close to the bench as well as at the bedside: involving service users in all phases of translational research

Aim:  The paper aims to develop a model of translational research in which service user and other stakeholder involvement are central to each phase. Background:  ‘Translational’ is the current medical buzzword: translational research has been termed ‘bench to bedside’ research and promises to fast-track biomedical advances in the service of patient benefit. Models usually conceive of translational research as a ‘pipeline’ that is divided into phases: the early phase is characterized as the province of basic scientists and laboratory-based clinical researchers; the later phases focus on the implementation, dissemination and diffusion of health applications. If service user involvement is mentioned, it is usually restricted to these later phases. Methods:  The paper critically reviews existing literature on translational research and medicine. The authors develop a theoretical argument that addresses why a reconceptualization of translational research is required on scientific, ethical and pragmatic grounds. Results:  The authors reconceptualize the model of translational research as an interlocking loop rather than as a pipeline, one in which service user and other stakeholder involvement feed into each of its elements. The authors demonstrate that for the ‘interlocking loop’ model of translational research to be materialized in practice will require changes in how health research is structured and organized. Conclusion:  The authors demonstrate the scientific, ethical and pragmatic benefits of involving service users in every phase of translational research. The authors’ reconceptualized model of translational research contributes to theoretical and policy debates regarding both translational research and service user involvement