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Coordination: Matthias Braun
Funded by: Bundesministerium für Bildung und Forschung

Own Data examines the challenges in dealing with “ownership” / “right to” data in systems medicine from an interdisciplinary perspective. The analysis of the ethical, legal and societal background concepts represents an essential research task for the further development of systems medicine. One of the central key concepts in this context is the question of who actually holds what claims and rights to data, which protection concepts are important, and to what extent they are effective. Last but not least, Own Data poses the question of what a future (international) governance strategy for dealing with big data in systems medicine might look like. At the heart of Own Data is a major international conference to be held in Erlangen/Nuremberg in March 2021.

Coordination: Matthias Braun
Researcher: Max Tretter
Funded by: Bundesministerium für Bildung und Forschung

The processes of digitalization and the application of artificial intelligence are shaping and changing both health research and medical practice. The speed and depth of these developments require considerations of responsible, effective and differentially sensitive governance.
CwiC is an interdisciplinary research project that aims to narrow the gap between basic normative theory formation and applied system design at the interface of science, society and technology. The project is based on a general anthropological and sociological basic idea: mutual recognition, which is essential for us as a society and as individuals, is closely linked to our common uncertainty about the future.
The joint project is funded by the BMBF for three years and consists of a legal (Steffen Augsberg, Gießen), an ethical (Matthias Braun, Erlangen) and a behavioural-economic (Nora Szech, Karlsruhe) subproject.

Coordination: Matthias Braun
Researcher: Hannah Bleher
Funded by: Bundesministerium für Bildung und Forschung

SMART Start focuses on improving and simplifying the prevention and care of pregnant women. Sensory applications such as fitness trackers and smartwatches are now finding their way into everyday life. The project investigates how these techniques and the data obtained from them can be used in regular prenatal care. Among other things, artificial intelligence and machine learning will be used for this purpose. In addition to the patients, the medical care system in general could also benefit from this.
The interdisciplinary research project is being carried out jointly by experts from medicine, computer science, ethics, psychology, and health economics. In addition, the focus is on clinical usability, social acceptance, compliance of the actors involved and the further development of sensory techniques as well as the associated ethical, medical law and economic questions.

Coordination: Matthias Braun / Peter Dabrock
Funded by: Bundesministerium für Bildung und Forschung

Genomic factors are responsible for 20–30% of the most common solid tumors, with current “-omics” analyses demonstrating the interaction of genomic and non-genomic risk factors and thus the complexity of tumor diseases. The steadily advancing identification of the factors involved and their complex interactions allow increasingly concrete predictions of disease risks and potential disease progression.
Compared to other tumor types, the most comprehensive data on genomic factors are available for breast cancer. Genome-wide association studies (GWAS) and, more recently, exome sequencing allow, on the one hand, to assign identified genomic factors to different risk intensities (low, moderate, high) and, on the other hand, to use these risk factors in their various combinations for the increasingly precise determination of individual disease risks. With this step towards a truly individualised medicine, a number of different, closely interlinked ethical, psychosocial, legal and health economic questions arise. For example, it is as yet unclear what consequences this medical-scientific development may have for everyday clinical practice, whether – and if so, which – preventive measures are not only adequate and effective at what time and with what degree of risk or subtype and what expected clinical course, but should also be borne by the community of solidarity, or on what legal basis appropriate measures can be taken. Because of the steering effect of the concept of disease on the health care system, this point in particular once again clearly points out the fundamental conceptual questions associated with the most recent scientific developments outlined above. These challenges, not least in view of the continuing high demand for counselling, prevention and prophylaxis, which has already been described as the “Jolie effect”, will be dealt with in an interdisciplinary manner in the network proposed for funding, based on the paradigm of breast cancer. The aim is to define medical, psychosocial, ethical, socio-legal and health economic benchmarks and, on this basis, to develop a matrix that can serve as a basis for the health system and political control of the identified requirements.
To work towards this goal, the consortium has at its disposal the world’s largest scientifically recorded cohort of persons at risk for breast and ovarian cancer. Extensive genetic, non-genetic, anamnestic and prospective data on the effectiveness of various prophylactic and preventive measures were collected in both cross-sectional and longitudinal studies. These data are used to model and process the identified ethical, psychosocial, socio-legal and health economic aspects.

Coordination: Matthias Braun / Peter Dabrock
Funded by: Bayerische Forschungsstiftung

Coordination: Patrik Hummel / Matthias Braun / Peter Dabrock
Funded by: Bundesministerium für Bildung und Forschung

Synthetic Biology (SB) as one of the currently leading fields of so-called emerging biotechnologies does not only promise new scientific insights into the organization of complex systems as well as possible applications for societal challenges but does also evoke several ethical, societal and governmental challenges. Within the first funding period we focus on the ethical questions colligated with SB on the one hand and the societal and especially participatory questions linked with the roots of SB as a part of the Do-it-Yourself-Biology movement as well as a citizens science approach. During the second funding period we will proceed with the work on developing modes for a governmental frame of responsible research and innovation in Synthetic Biology. Furthermore, we will continue with the started work on technological innovation and modes of public participation at the interface of science and society as well as figure out the role of philosophical and theological concepts in dealing with processes of developing a synthetic cell.

Coordination: Peter Dabrock / Matthias Braun / Patrik Hummel
Funded by: Bundesministerium für Gesundheit

DABIGO addresses the question of how the handling of individual (health) data can be responsibly designed in times of Big Data. The aim is to develop ethical and legal guidance markers for the development of a multidimensional concept of data sovereignty in clinical research and care. Methodologically, the connection to this field of application, following the approach of a concrete ethics, is ensured by linking the ethical and legal questions with an internationally leading clinical case. Within the framework of the PRAEGNANT network, high-volume data streams are brought together at the Women’s Hospital of the University Hospital Erlangen with the aim of significantly improving cancer prediction, diagnosis and therapy. The data streams consist of whole-genome sequencing data of tumor and germline, with a size of 250-500 GB and about 6 billion variables per patient, as well as lifestyle data of the patients and finally clinical and epidemiological data. The non-genomic data contain about 500-600 variables.
In the clinical case outlined, Big Data is used firstly to find out which clinical studies might be most suitable for which patients. While this can still be done with simple database queries, the second goal is to use the information to support therapy decisions in everyday clinical practice. Thirdly, so-called deep learning processes have already shown that certain indications can be set with a relatively high degree of reliability on the basis of existing information using computer algorithms.
One of the main governance challenges in dealing with big-data-driven changes in the health care system is that the increasing complexity and self-activity of big-data applications is massively changing the access and control options for both data donors and data users in the health care sector. But how must ethical criteria look like in which legal framework in order to enable both a responsible use of the data and to be able to address the possible challenges for clinical big data use in a sustainable manner with regard to both data donors and data users?

Coordination: Peter Dabrock
Funded by: Bundesministerium für Bildung und Forschung

The transformation of energy systems presents Germany with enormous political, economic and technological challenges. To support the transformation of energy supply, the Academies of Science have launched the “Energy Systems of the Future” initiative in 2013. In this three-year project, experts from various disciplines analysed the challenges of energy system transformation and described possible solutions.
In a second project phase, the Academies of Science are continuing the joint initiative under the leadership of acatech. In interdisciplinary working groups, around 100 experts are working out options for action on the way to an environmentally compatible, secure and affordable energy supply.