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Dagstuhl Perspectives Workshop 13342

ICT Strategies for Bridging Biology and Precision Medicine

( Aug 18 – Aug 23, 2013 )

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It is a well-known and much deplored fact that, despite great efforts, much of the overwhelming current progress in bio-medical research does not easily find its way to the bedside: While tools for generating ever better information regarding the individual makeup of a patient are becoming widely available, the sheer amount of data resulting from these tools often is too large to be useful to medical practitioners. So, clinicians should better be equipped with means

  • to easily annotate, exchange, and jointly interpret their patients' data,
  • to specifically search for the most relevant insights exactly when needed,
  • and to discuss the resulting implications for their clinical work,

taking into account all that can be learned from the various databases and tools the net provides.

Remarkably, there is a growing international consensus that the missing-context aware computing infrastructure can be established using modern integrative ICT-platform solutions for connecting bioscience and clinical work: The European ITFoM initiative urges the EU to provide a revolutionary ICT that revolutionises medicine. And a recent report of the National Academies of the USA suggests to create an integrative ICT-platform for a Knowledge Network of Disease that integrates the rapidly expanding range of information on the causes of disease and would allow researchers, health-care providers, and the public to share and update this information.

Such a platform could be used to optimally exploit the full potential of current business-IT alignment strategies, forming flexible and extendable IT architectures that respond to explicit governance needs, achieving the level of semantic interoperability needed for systematic de-coupling of services and mediation of conflicts, assignment and observance of rights and roles, activity monitoring and object management, assured security, and task-dependent dynamic modification of rules so as to making change and improvement a daily routine.

Furthermore, as time is still the most precious resource (also) in medical care, we need to find out how to design intelligent ICT so as to simplify the practitioners' professional life, not to overburden it with additional requests, and to save, not to waste their time. Indeed, young medical professionals are already dreaming of a de-digitalization of medicine as they tend to see ICT in hospitals as a curse, not a blessing for medical care. There is also a very specific requirement that ICT systems be patient-facing, very much in the same way physicians are, but this is a feature emerging mostly without the benefit of systematic study and planning. So, there is an imminent danger that inadequate design of medically oriented ICT will actually be counter-productive, not enhancing CS-application in medicine, but derailing it.

To discuss these perspectives and their consequences for IT development and for health care in some depth, we intend to bring together participants of the two former Dagstuhl Seminars on “Structure Discovery in Biology” with colleagues from the ITFoM and the US initiative as well as representatives from e.g. the Cancer Genome Atlas, the International Cancer Genome Consortium, the Conference on Semantics in Healthcare and Life Science, the Semantic Web Applications and Tools for Life Science group, the GI/GMDS one-day workshop on Supporting Translational and Personalized Medicine with SOA, Grid, and Cloud (September 2012), and similar workshops in China.

Jointly with these colleagues from mathematics, computer science, biology, and medicine, we want to explore in this workshop how ICT can be used in medical care to bridge the widening gap between biomedical research and daily clinical routine. The result of our workshop will be a Dagstuhl Manifesto detailing the open issues and research perspectives for the near future.

Suggested topics for discussion

  • The virtual oncology (diabetes,...) patient in medical practice
  • Virtualisation in drug development
  • Parallel toponome decoding and genome sequencing to asses emergent properties of chronic diseases and disease mechanisms
  • Studying the dynamics of disease progression and implications for disease mechanisms
  • A systems approach to blood and tissue diagnostics – There are really some outstanding recent results using proteins as well as mRNAs and miRNAs.
  • The integration and modeling of multi-omic data from disease and its implications for diagnosis and therapy
  • Family genome sequencing--and the use of Next Generation sequencing to find disease genes
  • Sequencing of genomes from tumors and its implications for therapy and disease stratification
  • The stratification of disease into discrete subtypes and implications for diagnosis and therapy
  • Assays for wellness
  • Architectures and APIs for user governed ICT
  • Big Data: What can it tell us?
  • The stratification of disease into discrete subtypes and implications for science
  • Fusing bioimaging data with clinical and molecular information (for enhancing a systems view of disease)
  • Does the complexity of precision medicine require new ways of medical training?
  • Precision medicine and evidence-based guidelines: complementary or incompatible?

Please, propose further topics you would like to see discussed.


Water, water, everywhere, nor any drop to drink. So goes Coleridge's Rime of the Ancient Mariner. Until recently, the same went for data: everywhere, but not of much use so far, neither for deriving new medical insights nor for improving medical care.

However, three key developments currently help to overcome this problem: the rapid adoption of electronic medical records [1] the dramatic advances in molecular biology [2] and, just as dramatic, the growing pervasiveness of social computing environments combined with a new attitude towards participatory health management [3,4,5]. The result is an exciting medley of initiatives devoted to supporting healthcare related information flow ranging from patient-facing resources such as PatientsLikeMe [6] to initiatives such as MD-Paedigre [7](EU's FP7) that provides a physician-centric sort of ' PatientsLikeMine' analogue addressing treatment choices in paediatrics.

Managing the creative deconstruction [8] involved in advancing towards systems medicine requires fundamentally changing the use of ICT in both, healthcare and biomedical research. It requires in particular to take account of the new paradigm of web-centric computing which is a basic prerequisite for all these initiatives.

Reflecting these concerns, a Dagstuhl Perspectives Workshop on ICT Strategies for Bridging Biology and Medicine was held to discuss a wide range of fundamental and foundational issues. These ranged from architectural considerations to data-access policies including Open/Linked Data, the Semantic Web, Pervasive Hardware Ecosystems, Medical Clouds, Patient-Participation Frameworks, 'Healthcare 4.0$', Analytical Tools, and Medical Education Clearly, the required changes can only be achieved by initiatives of a broader scale and scope than what can be accommodated within the existing academic organisations. They need to always involve all stakeholders in the healthcare environment. In response to these challenges, the discussions led to the following theses and postulates:

  1. An open-data policy for healthcare-related information systems is a fundamental and urgent imperative.
  2. Following the business-IT alignment paradigm [9], healthcare should -- on all levels -- be supported by secure IT-platforms enabling clinical workflow engines that map healthcare-related processes while integrating pertinent data-analysis, visualisation, and engineering tools.
  3. Such platforms should also take full advantage of advances provided by cloud services, pervasive computing ecosystems, and the semantic web.
  4. The participatory potential of the Web should be exploited to advance new forms of partnership in the healthcare environment.
  5. The acquisition of ICT literacy must become a required part of biomedical education.
  6. Specifically in Germany, the Bundesnetzagentur should be encouraged to setting up a Working Group Medizinische Netze to explore options for a Medical Cloud within the German healthcare environment.
  1. Tracy D. Gunter and Nicolas P. Terry The Emergence of National Electronic Health Record Architectures in the United States and Australia: Models, Costs, and Questions. J Med Internet Res 7:1 (2005). DOI:10.2196/jmir.7.1.e3.
  2. Susan Desmond-Hellmann et al. Toward Precision Medicine: Building a Knowledge Network for Biomedical Research and a New Taxonomy of Disease. National Research Council (US), Committee on A Framework for Developing a New Taxonomy of Disease. The National Academies Press, Washington D.C., USA (2011).
  3. Wikipedia.
  4. Barbara A. Israel et al. Community-based participatory research: policy recommendations for promoting a partnership approach in health research. Education for Health, 14:2 (2001):182--197.
  5. Melanie Swan. Emerging Patient-Driven Health Care Models: An Examination of Health Social Networks, Consumer Personalised Medicine and Quantified Self-Tracking. Int. J. Environ. Res. Public Health 6 (2009):492--525. DOI:10.3390/ijerph6020492.
  6. Ben Heywood et al.
  7. Bruno Dallapiccola et al. The European Commission.
  8. Eric J. Topol. The Creative Destruction of Medicine: How the Digital Revolution Will Create Better Health Care. Basic Books, New York, NY, USA (2012).
  9. Wim van Grembergen and Steven De Haes. Enterprise Governance of IT: Achieving Strategic Alignment and Value. Springer, New York Heidelberg Dordrecht London (2009).
Copyright Jonas S. Almeida, Andreas Dress, Titus Kühne, and Laxmi Parida

  • Jonas S. Almeida (University of Alabama - Birmingham, US) [dblp]
  • Bernhard Balkenhol (infinity³ GmbH - Gütersloh, DE) [dblp]
  • Mark Braunstein (Georgia Institute of Technology - Atlanta, US) [dblp]
  • Robert Burk (Yeshiva University - New York, US) [dblp]
  • Stefan Decker (National University of Ireland - Galway, IE) [dblp]
  • Helena F. Deus (Foundation Medicine, Inc. - Cambridge, US) [dblp]
  • Andreas Dress (Shanghai Institutes for Biological Sciences, CN & infinity3, DE) [dblp]
  • Jochen Dreß (DIMDI - Köln, DE)
  • David Gilbert (Brunel University, GB) [dblp]
  • Anja Hennemuth (Fraunhofer MEVIS - Bremen, DE) [dblp]
  • Scott Kahn (Illumina - San Diego, US) [dblp]
  • Ina Koch (Goethe-Universität - Frankfurt a. M., DE) [dblp]
  • Titus Kühne (Deutsches Herzzentrum, DE) [dblp]
  • Hans Lehrach (MPI für Molekulare Genetik - Berlin, DE) [dblp]
  • Pietro Lio (University of Cambridge, GB) [dblp]
  • Markus Löffler (Universität Leipzig, DE) [dblp]
  • Wolfgang Maaß (Universität des Saarlandes, DE) [dblp]
  • Klaus Maisinger (Illumina - United Kingdom, GB)
  • Eric Neumann (Foundation Medicine, Inc. - Cambridge, US) [dblp]
  • Laxmi Parida (IBM TJ Watson Research Center - Yorktown Heights, US) [dblp]
  • Alex Pothen (Purdue University - West Lafayette, US) [dblp]
  • Eric Prud'hommeaux (MIT - Cambridge, US) [dblp]
  • Joel Saltz (Emory University, US)
  • Walter Schubert (Universität Magdeburg, DE) [dblp]
  • Andrea Splendiani (intelliLeaf - London, GB & DERI - Galway, IE) [dblp]
  • Marc Van Regenmortel (IREBS - Illkirch, FR)
  • Susana Vinga (Technical University of Lisboa, PT) [dblp]
  • Peter Walden (Charité - Berlin, DE)
  • Zhenbing Zeng (East China Normal University - Shanghai, CN) [dblp]

  • bioinformatics
  • data bases / information retrieval
  • world wide web / internet

  • translational medicine
  • precision medicine
  • systems medicine
  • systems biology
  • genomics
  • proteomics
  • transcriptomics
  • computational biology
  • algorithmic bioinformatics
  • pattern discovery
  • integrative communication architecture
  • SOA
  • cloud
  • grid