§64e - The model project according to § 64e of the German Social Code (SGB V) aims to evaluate and implement innovative healthcare approaches to improve medical care delivery and patient outcomes. This project is based on broad genome sequencing as part of an structured clinical treatment procedure, followed by the integration of clinical and genomic data in a data infrastructure that allows for analysis of the data gathered to improve medical care. The goal is to create a framework for testing new models of care that can lead to better efficiency and effectiveness. By facilitating research and development in these areas, the project seeks to identify best practices and inform future healthcare policies.

DIFUTURE is one of four consortia selected by the German Ministry of Education and Research for financing during the Medical Informatics Initiative's development and networking phase. DIFUTURE seeks to provide clinicians and medical researchers with data that is comprehensive in both depth and breadth. We'll seek to speed up innovation, enhance health-care systems, and provide decision-making assistance, all of which will benefit patients. Data sharing and integration will be critical in the future of medicine, but they will necessitate a high level of data protection. DIFUTURE prioritizes privacy, security, and patient confidence. Novel ways are sought to provide a very high degree of security. The Technical University of Munich (TUM) and its University Medical Center Rechts der Isar, Ludwigs-Maximilians-Universität München (LMU) and Munich University Medical Center, Eberhard-Karls-Universität Tübingen (EKUT) and Tübingen University Medical Center, Augsburg University und Ulm University (UU) and Ulm University Medical Center have all joined forces to form DIFUTURE in 2019. Saarland University and Saarland University Medical Center, as well as Regensburg University Medical Center will became partners in 2022. Data Integration Centers at all sites are setup to achieve interoperability.

ZPM Four Centers for Personalized Medicine (ZPM) at the university hospitals of Freiburg, Heidelberg, Tuebingen and Ulm in Baden-Wuerttemberg have joined forces to incorporate Personalized Medicine into daily patient treatment. Common criteria and coordinated diagnostic methodologies serve as the foundation for optimal therapeutic options for all ZPM patients. We are building a care network with regional partners to enhance the care of patients with advanced malignancies and inflammatory disorders. The network will be expanded in the future to encompass more disease areas.

Bed capacity dashboard Interactive web dashboard to show realtime changes of bed capacites. Based on wekan (https://wekan.github.io/), extended with functionality for printing, exporting and automatic calculation of bed capacities.

CoCoV dashboard An interactive web dashboard provides an assessment of the reported COVID-19 vaccination-related adverse effects. At regular intervals, the data is transferred anonymously and securely.

AMBAR - Alteration annotations for Molecular tumor BoARds Personalized medicine and decision-making for cancer therapy rely on molecular profiling from sequencing data in combination with annotations from knowledge bases, evidence, and experts. Molecular tumor boards (MTBs) are becoming more common in clinical practice for therapeutic approaches and bring together physicians, clinicians, and scientists with diverse expertise. However, for MTBs, data analysis and documentation are still time-consuming and difficult to maintain, especially given the limited tools available for the complexity and volume of information. To overcome these limitations, we developed an interactive web application AMBAR (Alteration annotations for Molecular tumor BoARds) for therapeutic decision-making support. We streamlined and tailored the workflow from results of primary sequencing analysis to annotation and visualization in a customizable user interface. Different knowledge bases enrich alterations in interactive tables that allow filtering, rearranging rows and columns, and adding expert knowledge. For decision support, we optimized and personalized an evidence table for alterations. Levels of evidence for therapeutic drugs, their source, publication, and links to Clinical Trails are displayed to allow discussion and decision support for personalized therapy. One can quickly visualize and get an overview of a patient's mutational landscape and signature in an ideogram plot and stacked bar plots for collected alterations. Furthermore, one can export annotated variants and mutations as well as custom notes and selections in different interoperable formats. These may then be imported into the documentation systems of clinical information systems. AMBAR is an R shiny-based application that allows customization, interactive filtering, visualization, the inclusion of expert knowledge, and export to clinical systems of annotated mutations. Software can be found here: AMBAR

CTest - an online system to track test results: The software uses individualized QR-codes to offer testees with a browser-based online status update (and web links). CTest does not necessitate the installation of any programs or the creation of user accounts. The application generates cryptographically secure tracking IDs and does not collect any personal information. The major goal of this strategy was to alleviate the pressure on clinical personnel during the COVID-19 crisis and to enable for quick and near-instantaneous transmission of results to testees. The source code can be found at CTest

MRA - Mutation Resistance Analyzer: A tool linking human cytomegalovirus drug resistance mutations to resistance phenotypes. After sequencing alignment with SWAT algorithm, in a result view mutations like insertions, deletions, frameshifts and stop-codons are listed in tables. Positions of mutations are visualized in an alignment graph. If additional information about a mutation is found in the databases, it is indicated by pie charts representing (different) hypothesis of the publication(s). The web application is available at MRA

Spada F., Rosenwald A., Klapper W., Feller A., Fend F., Ott G., Fürstberger, A., Barth T., Möller P. Histomorphologic spectrum of nodal marginal zone lymphoma as defined by its methylome. American Journal of Clinical Pathology aqae120 ,2024.https://doi.org/10.1093/ajcp/aqae120

Menzel, M., Martis-Thiele, M., Goldschmid, H., Ott, A., Romanovsky, E., Siemanowski-Hrach, J., ...Fürstberger, A.,..., Stenzinger, A. Benchmarking Whole Exome Sequencing in the German Network for Personalized Medicine. European Journal of Cancer 211: 114306, 2024. https://doi.org/10.1016/j.ejca.2024.114306

Menzel M, Ossowski S, Kral S, Metzger P, Horak P, Marienfeld R, Borries M, Wolter S, Ball M, Neumann O, Armeanu-Ebinger S, Schroeder C, Matysiak U, Goldschmid H, Schipperges V, Fürstberger A, Allgäuer M, Eberhardt T, Niewöhner J, Blaumeiser A, Ploeger C, Haack TB, Tay TKY, Kelemen O, Pauli T, Kirchner M, Kluck K, Ott A, Renner M, Admard J, Bschweind A, Lassmann S, Kestler HA, Fend F, Illert AL, Werner M, Möller P, Seufferlein TTW, Malek N, Schirmacher P, Fröhling S, Kazdal D, Budczies J, Stenzinger A. Multicentric pilot study to standardize clinical whole exome sequencing (WES) for cancer patients. npj Precis Oncol 7: 106, 2023. https://doi.org/10.1038/s41698-023-00457-x

Fürstberger, A., Ikonomi, N., Kestler, A.M., Marienfeld, R., Schwab, J.D., Kuhn, P., Seufferlein, T. and Kestler, H.A. AMBAR-Interactive alteration annotations for molecular tumor boards Computer Methods and Programs in Biomedicine, 240:107697, 2023. https://doi.org/10.1016/j.cmpb.2023.107697

Bareiß A, Uzun G, Mikus M, Becker M, Althaus K, Schneiderhan-Marra N, Fürstberger A, Schwab JD, Kestler HA, Holderried M, Martus P, Schenke-Layland K, Bakchoul T. Vaccine Side Effects in Health Care Workers after Vaccination against SARS-CoV-2: Data from TüSeRe:exact Study. Viruses-Basel 15(1):65, 2023. https://doi.org/10.3390/v15010065

Ganzinger M, Blumenstock M, Fürstberger A, Greulich H, Kestler HA, Marschollek M, Niklas C, Schneider T, Spreckelsen C, Tute E, Varghese J, Dugas M. Federated Electronic Data Capture (fEDC): Architecture and Prototype. J Biomed Inform,138: 104280, 2023. https://doi.org/10.1016/j.jbi.2023.104280

Hamberger M, Ikonomi N, Schwab JD, Werle SD, Fürstberger A, Kestler AMR, Holderried M, Kaisers UX, Steger F, Kestler HA. Interaction Empowerment in Mobile Health: Concepts, Challenges, and Perspectives. JMIR mhealth uhealth 10(4): e32696, 2022. https://doi.org/10.2196/32696

Waldenmaier M, Schulte L, Schönfelder J, Fürstberger A, Kraus JM, Daiss N, Seibold T, Morawe M, Ettrick T, Kestler HA, Kahlert C, Seufferlein T, Eiseler T. Comparative Panel Sequencing of DNA Variants in cf-, ev- and tumorDNA for Pancreatic Ductal Adenocarcinoma Patients. MDPI Cancers 14(4): 1074, 2022. https://doi.org/10.3390/cancers14041074

Stilp AC, Scherer M, König P, Fürstberger A, Kestler HA, Stamminger T. The chromatin remodeling protein ATRX positively regulates IRF3-dependent type I interferon production and interferon-induced gene expression. PLoS Pathog 18(8): e1010748, 2022. https://doi.org/10.1371/journal.ppat.1010748

Laut AK, Dorneburg C, Fürstberger A, Barth TFE, Kestler HA, Debatin KM, Beltinger C. CHD5 inhibits metastasis of neuroblastoma. Oncogene 41(5): 622-633, 2022. https://doi.org/10.1038/s41388-021-02081-0

Völkel G, Fürstberger A, Schwab JD, Werle SD, Ikonomi N, Gscheidmeier T, Kraus JM, Groß A, Holderried M, Balig J, Jobst F, Kuhn P, Kuhn KA, Kohlbacher O, Kaisers UX, Seufferlein T, Kestler HA. Patient empowerment during the COVID-19 pandemic: Ensuring safe and fast communication of test results. J Med Internet Res 23(6): e27348, 2021. https://doi.org/10.2196/27348

Schwab JD, Schobel J, Werle SD, Fürstberger A, Ikonomi N, Szekely R, Thiam P, Hühne R, Jahn N, Schuler R, Kuhn P, Holderried M, Steger F, Reichert M, Kaisers UX, Kestler AMR, Seufferlein T, Kestler HA. Perspective on mHealth Concepts to Ensure Users’ Empowerment–From Adverse Event Tracking for COVID-19 Vaccinations to Oncological Treatment. IEEE Access 9: 83863-83875, 2021. https://doi.org/10.1109/ACCESS.2021.3087315

Kestler AMR, Kühlwein SD, Kraus JM, Schwab JD, Szekely R, Thiam P, Hühne R, Jahn N, Fürstberger A, Ikonomi N, Balig J, Schuler R, Kuhn P, Steger F, Seufferlein T, Kestler HA. Digitalization of adverse event management in oncology to improve treatment outcome—A prospective study protocol. PLoS One 16(6): e0252493, 2021. https://doi.org/10.1371/journal.pone.0252493

Schobel J, Volz M, Hörner K , Kuhn P, Jobst F, Schwab JD, Ikonomi N, Werle SD, Fürstberger A, Hoenig K, Kestler HA. Supporting Medical Staff from Psycho-Oncology with Smart Mobile Devices: Insights into the Development Process and First Results. Int J Environ Res Public Health 18(10): 5092, 2021. https://doi.org/10.3390/ijerph18105092

Völkel G, Laban S, Fürstberger A, Kühlwein SD, Ikonomi N, Hoffmann TK, Brunner C, Neuberg DS, Gaidzik V, Döhner H, Kraus JM, Kestler HA. Analysis, identification and visualization of subgroups in genomics. Brief Bioinform 22(3): bbaa217, 2021. https://doi.org/10.1093/bib/bbaa217

Seyfried F, Demir S, Hörl RL, Stirnweiß FU, Ryan J, Scheffold , Villalobos-Ortiz M, Boldrin E, Zinngrebe J, Enzenmüller S, Jenni S, Tsai YC, Bornhauser B, Fürstberger A, Kraus JM, Kestler HA, Bourquin JP, Stilgenbauer S, Letai A, Debatin KM and Meyer LH. Prediction of venetoclax activity in precursor B-ALL by functional assessment of apoptosis signaling. Cell Death Dis 10: 571, 2019. https://doi.org/10.1038/s41419-019-1801-0

Hühne H, Kessler V, Fürstberger A, Kühlwein S, Platzer M, Sühnel J, Lausser L, Kestler HA. 3D Network exploration and visualisation for lifespan data. BMC Bioinformatics 19(1): 390, 2018. https://doi.org/10.1186/s12859-018-2393-x

Fürstberger A, Maucher M, Kestler HA. Extended pairwise local alignment of wild card DNA/RNA-sequences using dynamic programming. J Stat Comput Simul 85(1): 3-13, 2015. https://doi.org/10.1080/00949655.2014.928294

Fürstberger A, Platzer M, Kestler HA. Googles DeepVariant: eine Methode für die Medizin- und Bioinformatik? BIOspektrum 24(3): 235-235, 2018.

Fürstberger A, Kraus JM, Kestler HA, (eds.). Classification 2016 — Abstracts of the 5th German-Japanese Symposium, Ulmer Informatik-Berichte 2016-05, Ulm University, Germany, 2016, ISSN 0939-5091.

Fürstberger A, Lausser L, Kraus JM, Schmid, M, Kestler HA, (eds.). Statistical Computing 2016 – Abstracts der 48. Arbeitstagung, Ulmer Informatik-Berichte 2016-04, Ulm University, Germany, 2016, ISSN 0939-5091.

Fürstberger A, Lausser, L, Kraus, JM, Schmid, M, Kestler, HA, (eds.). Statistical Computing 2015 – Abstracts der 47. Arbeitstagung, Ulmer Informatik-Berichte 2015-04, Ulm University, Germany, 2015, ISSN 0939-5091.