Miho, Enkelejda
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Enkelejda
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Miho, Enkelejda
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- PublikationThe real-world data challenges radar: a review on the challenges and risks regarding the use of real-world data(Karger, 2021) Grimberg, Frank; Asprion, Petra; Schneider, Bettina; Miho, Enkelejda; Babrak, Lmar; Habbabeh, Ali [in: Digital Biomarkers]Background: The life science industry has a strong interest in real-world data (RWD), a term that is currently being used in many ways and with varying definitions depending on the source. In this review article, we provide a summary overview of the challenges and risks regarding the use of RWD and its translation into real-world evidence and provide a classification and visualization of RWD challenges by means of the RWD Challenges Radar. Summary: Based on a systematic literature search, we identified 3 types of challenges – organizational, technological, and people-based – that must be addressed when deriving evidence from RWD to be used in drug approval and other applications. It further demonstrates that numerous different aspects, for example, related to the application field and the associated industry, must be considered. A key finding in our review is that the regulatory landscape must be carefully assessed before utilizing RWD. Key Messages: Establishing awareness and insight into the challenges and risks regarding the use of RWD will be key to taking full advantage of the RWD potential. As a result of this review, an “RWD Challenges Radar” will support the establishment of awareness by providing a comprehensive overview of the relevant aspects to be considered when employing RWD.01A - Beitrag in wissenschaftlicher Zeitschrift
- PublikationReal World Data - Technologies, Research Questions and Applications - Study in Cooperation - School of Business & School of Life Science(Fachhochschule Nordwestschweiz FHNW, 2019) Grimberg, Frank; Asprion, Petra; Schneider, Bettina; Miho, Enkelejda; Babrak, Lmar; Habbabeh, AliIn this research report of the University of Applied Sciences and Arts Northwestern Switzerland (FHNW), a classification of ‘Real World Data’ into the research landscape takes place. In addition, an identification of the still open research questions is done based on the fundamental principles and properties. The manifold potential of this relatively new data set is illustrated by a presentation of the already existing but also conceivable future application possibilities. Finally, the contribution of the FHNW, based on its specific competencies, to the further application of the dataset is shown.05 - Forschungs- oder Arbeitsbericht