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Updated: Apr 15, 2026

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
Published on: June 13, 2025
Inside the "Black Box" of a Knowledge Translation Program in Applied Health Research
Janet Heaton1, Jo Day2, Nicky Britten2
1University of Exeter, Exeter, United Kingdom j.heaton@exeter.ac.uk.
Abstract:
In this article, we present the findings of a participatory realistic evaluation of a 5-year program of health care research intended to promote the translation of knowledge into routine clinical practice. The program was one of the nine pilot Collaborations for Leadership in Applied Health Research and Care funded by the English National Institute for Health Research between 2008 and 2013. Our aim was to delineate the mechanisms by which, and circumstances in which, some projects carried out under the program achieved success in knowledge translation while others were frustrated. Using qualitative methods, we examined how closer collaboration between academics and clinicians worked in four purposefully chosen case studies. In a synthesis of the findings, we produced a "black box" model of how knowledge translation was enabled by the activation of nine mechanisms. These are summarized in the form of five simple rules for promoting knowledge translation through collaborations based on principles of coproduction.
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Translation is the process of synthesizing proteins from the genetic information carried by messenger RNA (mRNA). Following transcription, it constitutes the final step in the expression of genes. This process is carried out by ribosomes, complexes of protein and specialized RNA molecules. Ribosomes, transfer RNA (tRNA), and other proteins produce a chain of amino acids—the polypeptide—as the end product of translation.
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