Trademark MTZ® - A Profile of the Foundation

MTZ® in Germany: Promoting new dimensions of cutting-edge medical research by YOUNG SCIENTIFIC EXCELLENCE through an important prize, the M T Z® - A w a r d

„Innovative Multimedia Network Organization” in the Global Research Landscape“

For 20 years, the MTZ® Foundation has been working tirelessly to build a better future—a life of optimal health and aging with dignity. Issues of bioethics play a particularly important role in this effort.
Showing the future, discussing the future, and shaping the future—as an “innovative network organization,” the MTZ® Foundation is breaking new ground in research into the causes of disease and the development of medications.
The pace and drive of innovation in German science require us to always stay at the cutting edge. Since 2005, the Stifterverband für die Deutsche Wissenschaft has supported us—the founders Monika and Thomas Zimmermann (“MTZ”)— during the founding phase, through the legal recognition by the Düsseldorf District Government with a certificate dated October 16, 2006, the development of the foundation’s fundamental conceptual framework—including the “birth of the MTZ® Award”—and to this day in all matters pertaining to foundation law.

Basic research in the life sciences is conducted at leading German research institutions. To this end, we have established targeted, strong academic partnerships with Heinrich Heine University Düsseldorf as part of a research consortium with the German Diabetes Center (DDZ) of the Leibniz Association, the Max Planck Institute for Molecular Biomedicine in Münster, and the Helmholtz Association. In these outstanding German research hubs, young scientific talent finds an ideal research environment and can fully realize its potential.
We support groundbreaking findings in basic research from the laboratories—achieved, even in the digital world, through traditional “in vivo and in vitro” methods—in the fields of diabetes and cancer research, pluripotent stem cell research, tissue biology, vascular cell biology, and research on the coronavirus.

However, particularly when it comes to combating highly complex systemic diseases such as cancer and metabolic disorders (including diabetes and liver diseases), the MTZ® Foundation has, from the very beginning, embraced digital advancements in cutting-edge medical research and their immeasurable potential. Only the interplay of the three approaches—“in vivo, in vitro, and in silico”—is truly innovative and forward-looking.
In this regard, the Foundation aligns its scientific focus with the funding initiatives of its strongest partner, the Federal Ministry of Research, Technology, and Space (BMFTR). It complements the BMFTR’s project funding with targeted individual grants. The outstanding German research clusters funded by the BMFTR and their rising scientific talent have for years been synonymous with innovative and forward-looking research approaches.

Since 2007, support for medically oriented systems biology—as an extremely innovative research approach—in Germany has been closely linked to the MTZ® Foundation. The 2008 MTZ® Award for Medical Systems Biology was the first national award for early-career researchers in the field of medical systems biology in Europe.
The wealth of data on individual cellular components and functions—obtained at various levels of biological processes using the classical scientific research approach (genome, proteome, metabolome)—is integrated into a meaningful, broader, and in some cases new overall context in systems biology through mathematical, computer-aided modeling (“in silico”) and bioprocess engineering. The central question is how complex biological systems, with their interconnected subprocesses, can function. Only in this way can the regulation and control of biological systems, their controllability, and their systemic behavior be understood and further unraveled. Physicians, biologists, bioinformaticians, and natural scientists from other disciplines collaborate in an interdisciplinary manner. The resulting models make it possible to directly simulate strategies and further hypotheses experimentally. These simulations are increasingly replacing time-consuming experiments with cell tissues in the laboratory (including animal testing) and contribute to faster and more effective research results—the new dimension of basic life sciences research.

In this way, our understanding of the functions of complex biological systems is expanding, increasingly enabling science to identify—in great detail—malfunctions as the cause of serious diseases. It is thanks to systems biology that we are able, for example, to understand tumor biology—including the proteomic* and morphological* characteristics typical of each tumor—a dynamic process of knowledge acquisition that continues to this day. The same applies to systems biology research into the respective genotype* in diabetes. In recent years, this research has focused on the development of tumor and biomarkers, which are used for diagnosis in current clinical practice. These are relevant to treatment and thus also form the basis for the development of drugs and vaccines.
Genotype*:
proteomic*: the totality of all proteins
morphological*: cell structure in medical imaging, now implemented in multiplex high-resolution fluorescence images (including 3D)

World-class medical research, such as systems biology and the mathematical modeling of biological systems, is leading to an ongoing, dynamic accumulation of knowledge and is already generating vast amounts of data—“big data in medicine.” The medicine of the future is inconceivable without artificial intelligence. Intelligent algorithms play a crucial role in linking biological systems with digitized clinical patient data. Systems biology has established itself as the essential form of basic research and a “data provider.” It will continue to serve as a bridge for (systems) medicine, enabling the individualized treatment of diseases in clinical practice through AI-supported, medically relevant use cases. In science, systems biology and its significance as a translational research approach have become indispensable.

The first corresponding algorithms are already being tested in everyday clinical practice and will make it possible in future to tailor diagnostic options, treatment strategies or prevention approaches specifically for each person and at the right time. Deep learning/machine learning in medicine, for example in cancer treatment at German university hospitals, works as follows: the AI learns the systems biology genotype* of a tumor and, in a second step, how it changes based on the treatment data of many patients. This initially enables a verified individual diagnosis of the tumor.
This initially enables a verified individual diagnosis and, as the disease progresses, precise treatment taking into account the individual stage of the disease. Especially with regard to many undesirable side effects of cancer therapies, such treatment optimization leads to an increased quality of life.

The algorithms are continuously validated and further developed in innovative ways. The focus will be on proposing solutions to previously unresolved clinical questions or unsolved scientific obstacles related to specific use cases that appear particularly promising and worthwhile for in silico modeling but still require further development. This will initiate systems biology research projects on previously unknown tumor/biomarkers (signatures) and on increasingly high-quality imaging data, thereby contributing to the value creation of the use cases.