Prof. Dr. Klaus A. Kuhn leads DIFUTURE – one of the four consortia of the Medical Informatics Initiative selected for funding by the German Federal Ministry of Education and Research (BMBF). He researches digital and translational medicine, with a specific focus on integration and security architectures. From 1996 to 2004, he was Chair of the Institute of Medical Informatics at the University of Marburg. Since 2004, he has been Director of the Institute of Medical Informatics, Statistics and Epidemiology (IMedIS) at the Technical University of Munich – Dr. Fabian Prasser works at IMedIS and is the technical coordinator for DIFUTURE. His research focuses on big data in medicine, translational information integration and data protection. We spoke with Prof. Kuhn and Dr. Prasser about the consortium’s approach and the importance of biobanking within this.
Mr Kuhn, Mr Prasser, which specific approach are you taking with DIFUTURE?
Kuhn: DIFUTURE’s approach is based on concrete use cases. A step-by-step plan has been conceived accordingly to allow the methods and solutions developed to be transferred and refined further. The use cases consider various different diseases and primarily aim at concrete benefits for the patients. The needs of physicians and researchers are also important though.
Which use cases are you working on and how were they selected?
Prasser: The use cases for DIFUTURE follow a clear plan that foresees a number of implementation phases. Work already began in 2016 on achieving the optimal treatment of multiple sclerosis. The methods developed during this first use case have been transferred to the second use case on Parkinson’s disease since 2017. Use cases on cancer, strokes and cardiovascular diseases will be addressed later on in the project, from 2020. There are then plans to implement further use cases from 2022.
The DIFUTURE use cases were selected in an internal call with a subsequent multidisciplinary evaluation according to defined criteria. Important factors were the relevance of the question, preliminary work at the consortium locations, the consortium’s expertise and the data situation.
What is your vision? Could you give an example to explain this?
Kuhn: All DIFUTURE use cases aim to enable precision medicine. This is characterised by prediction-based, personalised prevention, diagnosis, treatment and aftercare with the active participation of citizens and patients. High-quality data and knowledge of comprehensive depth and breadth must be made available for research and patient care to achieve this.
The MS use case is a good example here: the aim is to adapt the medication to individual patients at the earliest possible stage. To this end, all kinds of data is being made available for cross-institutional analyses and the disease courses of people with MS compared. Special features and similarities are sought, which will allow the disease’s course to be predicted with different treatment alternatives.
Please explain briefly how you ensure data protection and security.
Prasser: The networked data usage makes comprehensive protective measures necessary. Patient trust and informed self-determination play a significant role in DIFUTURE. The consortium relies on state-of-the-art data protection and IT security concepts to ensure these. The modular structure of the DIFUTURE architecture supports the separation of data, tasks and responsibilities into different organisational and technical units, for example. Data exchange methods are selected specifically for each use case based on rigorous risk and threat analyses. DIFUTURE places particular emphasis on distributed data processing and remote analysis during which no individual data leaves the institutions’ sovereignty.
What measures are you taking to encourage patients to trust in innovative technology like yours?
Kuhn: Particularly in this regard, we consider DIFUTURE’s step-by-step, use case-driven approach to be very important. The data exchange within DIFUTURE also follows this step-by-step plan and thus clearly defined goals – to the benefit of our patients. Based on the aforementioned risk and threat analyses, it is possible to select specific analysis methods, which safeguard patients’ informed self-determination, for example.
What role does biobanking play in DIFUTURE?
Prasser: Biobanking and modern data types play a decisive role in the DIFUTURE use cases. Preliminary work from projects such as the m4 excellence cluster and BioMedBridges is as important as current projects on IT infrastructure for biobanks in which the DIFUTURE consortium partners are involved. The BMBF-funded German Biobank Alliance is a good example of this.
In your opinion, how could the cooperation between MII, the German Biobank Node and the German Biobank Alliance be enhanced?
Kuhn: The cooperation between MII, GBN and GBA is already good. Take the joint work on the “Biomaterial” extension module within MII’s national core data set, the exchange on tools and concepts as well as the plans for a joint pilot study, for instance. We’re on the right track with these. And we’re involved in GBA, too.
The interview was conducted by Verena Huth.
