Meeting the Challenges of Chronic Age-Related Diseases in Rural Areas

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The University Medicine Greifswald (UMG) will implement a state of the art Clinician Scientist program (CSP) that forms an essential building block for strengthening its profile as a center for translational research oriented towards the needs of patient care in rural areas in the future. Partners from the clinical departments of Cardiovascular Medicine, Neurology, and Oncology will join forces with the Institutes of Medical Biochemistry, Bioinformatics, and Community Medicine to address common, age-related diseases in both research and patient care. We will draw on extensive ongoing work on proteostasis, data mining methods, clinical trials and health services research, to offer internationally competitive research training and clinical skills to young Clinician Scientist (CS) fellows. In their scientific rotation, the CS fellows will acquire knowledge in applying cutting-edge scientific laboratory techniques and clinical trial methodology, as well as modern data mining and machine learning approaches to unravel mechanisms underlying cardiomyopathies, muscle wasting, frailty, dementia, delirium, and chronic myeloid neoplasms, and to develop novel therapeutic approaches for these conditions. In their clinical work, the CS fellows will enter a well-defined rotation scheme that will train them in interdisciplinary patient care for populations under study. The CSP will be embedded into the overall research agenda of the UMG, as defined in the strategic agenda “UMG 2026”, which specifies a focus on four main Research Platforms (Community Medicine, Molecular Medicine, Individualized Medicine and Digital Health), all of which will be integrated in the CSP, and the promotion of translational research and outreach into the rural community as constitutive elements for the profile of the UMG. In sum, all CSP projects will qualify and train the fellows in clinical and patient-related aspects, and empower them for an internationally competitive scientific track. In addition, by ensuring regular cohorts of highly motivated young clinician scientists, the CSP will sustainably boost the UMG’s efforts to identify molecular and clinical signatures of chronic age-related diseases, to use machine learning to harness digital data from the clinical information system for data-driven health research, and to develop digital diagnostic and therapeutic approaches for use in the community. The CSP outlined here will be sustainably anchored within the UMG, including CS fellow positions, advanced CS fellow positions, and the extensive accompanying seminar and workshop program.