gms | German Medical Science

64. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e. V. (GMDS)

Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie

08. - 11.09.2019, Dortmund

Using signaling pathway knowledge in a hospital setting: Extending the FHIR standard for health care data exchange

Meeting Abstract

Search Medline for

  • Florian Auer - University of Augsburg, Augsburg, Germany
  • Frank Kramer - University of Augsburg, Augsburg, Germany

Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie. 64. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e.V. (GMDS). Dortmund, 08.-11.09.2019. Düsseldorf: German Medical Science GMS Publishing House; 2019. DocAbstr. 321

doi: 10.3205/19gmds163, urn:nbn:de:0183-19gmds1633

Published: September 6, 2019

© 2019 Auer et al.
This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 License. See license information at



In modern Systems Medicine approaches the aim is to look at increasingly complex interactions of complete signaling pathways in order to get a more holistic view. Individualized treatment decisions and newly developed specialized drugs warrant the need to broaden the focus in precision medicine from singular biomarkers to pathways [1].

On the other hand, pathway databases offer vast amounts of knowledge on biological networks, freely available and encoded in semi-structured formats [2], [3]. The efficient re-use of pathway knowledge and its integration into bioinformatic analyses enables new insights for researchers in systems medicine.

However, the vast amount of published data on molecular interactions makes it increasingly challenging for life science researchers to find and extract the most relevant information. Currently, the tools to use this information and integrate it in a clinical context are still lacking [4]. To use this information, adaption to established specifications and standards for health care data exchange is essential.

Fast Healthcare Interoperability Resources (FHIR) [5] are modular and extendable components, building upon web standards and RESTful architectures for seamless information exchange. Currently, there's no complex data type available to represent networks within the FHIR framework, despite its increasing application in research. Here we present an extension of the existing FHIR specification, utilizing state of the art technology [6], [7] and well-established standard data models [8], [9], [10].

The authors declare that they have no competing interests.

The authors declare that an ethics committee vote is not required.


Chin L, Andersen JN, Futreal PA. Cancer genomics: from discovery science to personalized medicine. Nat Med. 2011 Mar;17(3):297–303.
Bader GD, Cary MP, Sander C. Pathguide: a pathway resource list. Nucleic Acids Res. 2006 Jan 1;34(Database issue):D504-506.
Schaefer CF, Anthony K, Krupa S, Buchoff J, Day M, Hannay T, et al. PID: the Pathway Interaction Database. Nucleic Acids Res. 2009 Jan;37(Database issue):D674–9.
Yang C, Chou TC, Chen YH. Bridging digital boundary in healthcare systems — An interoperability enactment perspective. Comput Stand Interfaces. 2019 Feb 1;62:43–52.
Bender D, Sartipi K. HL7 FHIR: An agile and RESTful approach to healthcare information exchange. In: Proceedings of CBMS 2013 - 26th IEEE International Symposium on Computer-Based Medical Systems; 2013 Jun 20-22; Porto, Portugal. 2013. p. 326–31.
R Development Core Team. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing; 2008 [cited 2017 May 9]. Available from: External link
Kramer F, Bayerlova M, Klemm F, Bleckmann A, Beissbarth T. rBiopaxParser - an R package to parse, modify and visualize BioPAX data. Bioinformatics. 2013 Feb 15;29(4):520–2.
Demir E, Cary MP, Paley S, Fukuda K, Lemer C, Vastrik I, et al. The BioPAX community standard for pathway data sharing. Nat Biotechnol. 2010 Sep;28(9):935–42.
Hucka M, Finney A, Sauro HM, Bolouri H, Doyle JC, Kitano H, et al. The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models. Bioinformatics. 2003 Mar 1;19(4):524–31.
Pratt D, Chen J, Welker D, Rivas R, Pillich R, Rynkov V, et al. NDEx, the Network Data Exchange. Cell Syst. 2015 Oct 28;1(4):302–5.