NCATS Inxight Drugs: a comprehensive and curated portal for translational research.

The United States has a complex regulatory scheme for marketing drugs. Understanding drug regulatory status is a daunting task that requires integrating data from many sources from the United States Food and Drug Administration (FDA), US government publications, and other processes related to drug development. At NCATS, we created Inxight Drugs (https://drugs.ncats.io), a web resource that attempts to address this challenge in a systematic manner. NCATS Inxight Drugs incorporates and unifies a wealth of data, including those supplied by the FDA and from independent public sources. The database offers a substantial amount of manually curated literature data unavailable from other sources. Currently, the database contains 125 036 product ingredients, including 2566 US approved drugs, 6242 marketed drugs, and 9684 investigational drugs. All substances are rigorously defined according to the ISO 11238 standard to comply with existing regulatory standards for unique drug substance identification. A special emphasis was placed on capturing manually curated and referenced data on treatment modalities and semantic relationships between substances. A supplementary resource 'Novel FDA Drug Approvals' features regulatory details of newly approved FDA drugs. The database is regularly updated using NCATS Stitcher data integration tool that automates data aggregation and supports full data access through a RESTful API.

Categorizing biomedical research: the basics of translation.

As biomedical research has evolved over the past century, the terminology employed to categorize it has failed to evolve in parallel to accommodate the implications of these changes. In particular, the terms basic research and translational research as used today in biomedicine seem especially problematic. Here we review the origins of these terms, analyze some of the conceptual confusions attendant to their current use, and assess some of the deleterious consequences of these confusions. We summarize that the distinction between basic and translational biomedical research is an anachronism. Elimination of this often contentious distinction would improve both the culture and the effectiveness of the scientific process, and its potential benefits to society.-Flier, J. S., Loscalzo, J. Categorizing biomedical research: the basics of translation.

Classification schemes for knowledge translation interventions: a practical resource for researchers.

BACKGROUND: As implementation science advances, the number of interventions to promote the translation of evidence into healthcare, health systems, or health policy is growing. Accordingly, classification schemes for these knowledge translation (KT) interventions have emerged. A recent scoping review identified 51 classification schemes of KT interventions to integrate evidence into healthcare practice; however, the review did not evaluate the quality of the classification schemes or provide detailed information to assist researchers in selecting a scheme for their context and purpose. This study aimed to further examine and assess the quality of these classification schemes of KT interventions, and provide information to aid researchers when selecting a classification scheme. METHODS: We abstracted the following information from each of the original 51 classification scheme articles: authors' objectives; purpose of the scheme and field of application; socioecologic level (individual, organizational, community, system); adaptability (broad versus specific); target group (patients, providers, policy-makers), intent (policy, education, practice), and purpose (dissemination versus implementation). Two reviewers independently evaluated the methodological quality of the development of each classification scheme using an adapted version of the AGREE II tool. Based on these assessments, two independent reviewers reached consensus about whether to recommend each scheme for researcher use, or not. RESULTS: Of the 51 original classification schemes, we excluded seven that were not specific classification schemes, not accessible or duplicates. Of the remaining 44 classification schemes, nine were not recommended. Of the 35 recommended classification schemes, ten focused on behaviour change and six focused on population health. Many schemes (n = 29) addressed practice considerations. Fewer schemes addressed educational or policy objectives. Twenty-five classification schemes had broad applicability, six were specific, and four had elements of both. Twenty-three schemes targeted health providers, nine targeted both patients and providers and one targeted policy-makers. Most classification schemes were intended for implementation rather than dissemination. CONCLUSIONS: Thirty-five classification schemes of KT interventions were developed and reported with sufficient rigour to be recommended for use by researchers interested in KT in healthcare. Our additional categorization and quality analysis will aid in selecting suitable classification schemes for research initiatives in the field of implementation science.

The development of a classification schema for arts-based approaches to knowledge translation.

BACKGROUND: Arts-based approaches to knowledge translation are emerging as powerful interprofessional strategies with potential to facilitate evidence uptake, communication, knowledge, attitude, and behavior change across healthcare provider and consumer groups. These strategies are in the early stages of development. To date, no classification system for arts-based knowledge translation exists, which limits development and understandings of effectiveness in evidence syntheses. PURPOSE: We developed a classification schema of arts-based knowledge translation strategies based on two mechanisms by which these approaches function: (a) the degree of precision in key message delivery, and (b) the degree of end-user participation. We demonstrate how this classification is necessary to explore how context, time, and location shape arts-based knowledge translation strategies. DISCUSSION: Classifying arts-based knowledge translation strategies according to their core attributes extends understandings of the appropriateness of these approaches for various healthcare settings and provider groups. The classification schema developed may enhance understanding of how, where, and for whom arts-based knowledge translation approaches are effective, and enable theorizing of essential knowledge translation constructs, such as the influence of context, time, and location on utilization strategies. LINKING EVIDENCE TO ACTION: The classification schema developed may encourage systematic inquiry into the effectiveness of these approaches in diverse interprofessional contexts.

Translational research in practice.

Readers will now be familiar with the notion of 'translational research'. According to its generally acknowledged progenitor, the National Institutes of Health (NIH) in the US, this is a kind of research agenda focused on translating or applying the research findings from basic/preclinical studies to human studies and perhaps most especially treatment trials; and, the translation of clinical research findings to the community so that evidence-based best practice is adopted.

A scoping review of classification schemes of interventions to promote and integrate evidence into practice in healthcare.

BACKGROUND: Many models and frameworks are currently used to classify or describe knowledge translation interventions to promote and integrate evidence into practice in healthcare. METHODS: We performed a scoping review of intervention classifications in public health, clinical medicine, nursing, policy, behaviour science, improvement science and psychology research published to May 2013 by searching MEDLINE, PsycINFO, CINAHL and the grey literature. We used five stages to map the literature: identifying the research question; identifying relevant literature; study selection; charting the data; collating, summarizing, and reporting results. RESULTS: We identified 51 diverse classification schemes, including 23 taxonomies, 15 frameworks, 8 intervention lists, 3 models and 2 other formats. Most documents were public health based, 55% included a literature or document review, and 33% were theory based. CONCLUSIONS: This scoping review provides an overview of schemes used to classify interventions which can be used for evaluation, comparison and validation of existing and emerging models. The collated taxonomies can guide authors in describing interventions; adequate descriptions of interventions will advance the science of knowledge translation in healthcare.

Methods for identifying translational researchers.

There is currently no generally accepted method for identifying the community of translational researchers when evaluating Clinical and Translational Science Centers. We use data from the multiyear evaluation of the University of Illinois at Chicago Center for Clinical and Translational Science (CCTS) to investigate the complexities of reliably identifying translational researchers. We use three methods to identify translational researchers: (1) participating in CCTS services and programs; (2) self-identifying as a translational researcher; and (3) engaging in activities that are characteristic of translational science. We find little overlap of these differently defined research groups. We conclude with a discussion of how the findings suggest challenges for evaluating translational science programs and the need for better definition, communication, and demonstration of translational science for scientists and evaluators.