scholarly journals Best Practices for Clinical and Translational Research and Implementation

2016 ◽  
Vol 9 (5) ◽  
pp. 231-232 ◽  
Author(s):  
DL Kroetz
Keyword(s):  
Best Practices ◽  
Translational Research ◽  
Clinical And Translational Research

scholarly journals Building capacity for collaborative research on opioid and other substance use disorders through the Clinical and Translational Science Award Program

2019 ◽  
Vol 4 (2) ◽  
pp. 81-89 ◽  
Author(s):  
Linda B. Cottler ◽  
Alan I. Green ◽  
Harold Alan Pincus ◽  
Scott McIntosh ◽  
Jennifer L. Humensky ◽  
...  
Keyword(s):  
Best Practices ◽  
Translational Research ◽  
Data Science ◽  
Academic Research ◽  
Translational Science ◽  
Timely Response ◽  
The Usa ◽  
Science Community ◽  
Landscape Survey ◽  
Clinical And Translational Research

AbstractThe opioid crisis in the USA requires immediate action through clinical and translational research. Already built network infrastructure through funding by the National Institute on Drug Abuse (NIDA) and National Center for Advancing Translational Sciences (NCATS) provides a major advantage to implement opioid-focused research which together could address this crisis. NIDA supports training grants and clinical trial networks; NCATS funds the Clinical and Translational Science Award (CTSA) Program with over 50 NCATS academic research hubs for regional clinical and translational research. Together, there is unique capacity for clinical research, bioinformatics, data science, community engagement, regulatory science, institutional partnerships, training and career development, and other key translational elements. The CTSA hubs provide unprecedented and timely response to local, regional, and national health crises to address research gaps [Clinical and Translational Science Awards Program, Center for Leading Innovation and Collaboration, Synergy paper request for applications]. This paper describes opportunities for collaborative opioid research at CTSA hubs and NIDA–NCATS opportunities that build capacity for best practices as this crisis evolves. Results of a Landscape Survey (among 63 hubs) are provided with descriptions of best practices and ideas for collaborations, with research conducted by hubs also involved in premier NIDA initiatives. Such collaborations could provide a rapid response to the opioid epidemic while advancing science in multiple disciplinary areas.

scholarly journals The gut microbiome of laboratory mice: considerations and best practices for translational research

2021 ◽  
Author(s):  
Aaron C. Ericsson ◽  
Craig L. Franklin
Keyword(s):  
Human Physiology ◽  
Best Practices ◽  
Gut Microbiota ◽  
Translational Research ◽  
Mouse Models ◽  
Gut Microbiome ◽  
Predictive Power ◽  
Environmental Influences ◽  
Pharmacological Intervention ◽  
Laboratory Mice

AbstractJust as the gut microbiota (GM) is now recognized as an integral mediator of environmental influences on human physiology, susceptibility to disease, and response to pharmacological intervention, so too does the GM of laboratory mice affect the phenotype of research using mouse models. Multiple experimental factors have been shown to affect the composition of the GM in research mice, as well as the model phenotype, suggesting that the GM represents a major component in experimental reproducibility. Moreover, several recent studies suggest that manipulation of the GM of laboratory mice can substantially improve the predictive power or translatability of data generated in mouse models to the human conditions under investigation. This review provides readers with information related to these various factors and practices, and recommendations regarding methods by which issues with poor reproducibility or translatability can be transformed into discoveries.

scholarly journals Participatory Needs Assessment and Action Planning for a Clinical and Translational Research Network

2020 ◽  
pp. 1-23
Author(s):  
LaKaija J. Johnson ◽  
Jolene Rohde ◽  
Mary E. Cramer ◽  
Lani Zimmerman ◽  
Carol R. Geary ◽  
...  
Keyword(s):  
Needs Assessment ◽  
Translational Research ◽  
Action Planning ◽  
Research Network ◽  
Clinical And Translational Research

scholarly journals Clinical and Translational Research and Community Engagement: Implications for Researcher Capacity Building

2012 ◽  
Vol 5 (4) ◽  
pp. 329-332 ◽  
Author(s):  
Linda Sprague Martinez ◽  
Beverley Russell ◽  
Carolyn Leung Rubin ◽  
Laurel K. Leslie ◽  
Doug Brugge
Keyword(s):  
Community Engagement ◽  
Translational Research ◽  
Capacity Building ◽  
Clinical And Translational Research

High-Quality Peer Review of Clinical and Translational Research

2021 ◽  
Vol 78 (15) ◽  
pp. 1564-1568
Author(s):  
Fred M. Kusumoto ◽  
John A. Bittl ◽  
Mark A. Creager ◽  
Harold L. Dauerman ◽  
Anuradha Lala ◽  
...  
Keyword(s):  
Translational Research ◽  
Peer Review ◽  
High Quality ◽  
Clinical And Translational Research

ARGO, Automatic Record Generator for Oncology: a natural language process-based tool to capture pathology features from onco-hematological reports (Preprint)

2021 ◽  
Author(s):  
Gian Maria Zaccaria ◽  
Vito Colella ◽  
Simona Colucci ◽  
Felice Clemente ◽  
Fabio Pavone ◽  
...  
Keyword(s):  
Natural Language ◽  
Translational Research ◽  
Language Processing ◽  
Character Recognition ◽  
Web Application ◽  
Optical Character Recognition ◽  
Anatomical Site ◽  
Cell Of Origin ◽  
Molecular Features ◽  
Clinical And Translational Research

BACKGROUND The unstructured nature of medical data from Real-World (RW) patients and the scarce accessibility for researchers to integrated systems restrain the use of RW information for clinical and translational research purposes. Natural Language Processing (NLP) might help in transposing unstructured reports in electronic health records (EHR), thus prompting their standardization and sharing. OBJECTIVE We aimed at designing a tool to capture pathological features directly from hemo-lymphopathology reports and automatically record them into electronic case report forms (eCRFs). METHODS We exploited Optical Character Recognition and NLP techniques to develop a web application, named ARGO (Automatic Record Generator for Oncology), that recognizes unstructured information from diagnostic paper-based reports of diffuse large B-cell lymphomas (DLBCL), follicular lymphomas (FL), and mantle cell lymphomas (MCL). ARGO was programmed to match data with standard diagnostic criteria of the National Institute of Health, automatically assign diagnosis and, via Application Programming Interface, populate specific eCRFs on the REDCap platform, according to the College of American Pathologists templates. A selection of 239 reports (n. 106 DLBCL, n.79 FL, and n. 54 MCL) from the Pathology Unit at the IRCCS - Istituto Tumori “Giovanni Paolo II” of Bari (Italy) was used to assess ARGO performance in terms of accuracy, precision, recall and F1-score. RESULTS By applying our workflow, we successfully converted 233 paper-based reports into corresponding eCRFs incorporating structured information about diagnosis, tissue of origin and anatomical site of the sample, major molecular markers and cell-of-origin subtype. Overall, ARGO showed high performance (nearly 90% of accuracy, precision, recall and F1-score) in capturing identification report number, biopsy date, specimen type, diagnosis, and additional molecular features. CONCLUSIONS We developed and validated an easy-to-use tool that converts RW paper-based diagnostic reports of major lymphoma subtypes into structured eCRFs. ARGO is cheap, feasible, and easily transferable into the daily practice to generate REDCap-based EHR for clinical and translational research purposes.

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