An Approach for Managing Clinical Trial Applications Using Semantic Information Models

  • Hans-Georg Fill
  • Ilona Reischl
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 43)

Abstract

The management of clinical trial applications by public authorities is a complex process involving several regulations, actors, and IT systems. In this paper we present a modeling approach based on semantic information models that supports this process. In particular, the approach can be used for the generation of user-centric visualizations, performance and compliance analyses and the distribution of the contained knowledge within an organization and to third parties. The approach has been developed together with AGES PharmMed and applied to their core processes.

Keywords

Clinical trials process management semantic information visualization 

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References

  1. 1.
    Kyle, M.: Pharmaceutical Price Controls and Entry Strategies. The Review of Economics and Statistics 89(1), 88–99 (2007)CrossRefGoogle Scholar
  2. 2.
    Sauer, C., Sauer, R.: Is it possible to have cheaper drugs and preserve the incentive to innovate? The benefits of privatizing the drug approval process. Journal of Technology Transfer 32, 509–524 (2007)CrossRefGoogle Scholar
  3. 3.
    Sung, N., et al.: Central Challenges Facing the National Clinical Research Enterprise. The Journal of the American Medical Association 289(10), 1278–1287 (2003)CrossRefGoogle Scholar
  4. 4.
    Himmelreich, J.: A compliance office for heavily regulated enterprises – a best practice approach meeting US FDA requirements. BT Technology Journal 25(1), 41–49 (2007)CrossRefGoogle Scholar
  5. 5.
    Karagiannis, D., Kuehn, H.: Metamodeling platforms. In: Bauknecht, K., Min Tjoa, A., Quirchmayer, G. (eds.) EC-Web 2002. LNCS, vol. 2455, p. 182. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  6. 6.
    Fill, H.G.: Visualisation for Semantic Information Systems. Gabler (2009)Google Scholar
  7. 7.
    Favre, J.-M.: Foundations of meta-pyramids: Languages vs. metamodels - episode ii: Story of thotus the baboon. In: Bzivin, J., Heckel, R. (eds.) Language Engineering for Model-driven Software Development, Dagstuhl, Germany, IBFI Dagstuhl (2005)Google Scholar
  8. 8.
    Keller, G., Nuettgens, M., Scheer, A.W.: Semantische Prozessmodellierung auf der Grundlage Ereignisgesteuerter Prozessketten (EPK). Veroeffentlichungen des Instituts für Wirtschaftsinformatik (IWi), Universiẗa des Saarlandes Heft 89, 29 (1992), http://www.iwi.uni-sb.de/nuettgens/Veroef/Artikel/heft089/heft089.pdf Google Scholar
  9. 9.
    Herbst, J., Karagiannis, D.: Integrating machine learning and workflow management to support acquisition and adaptation of workflow models. Intelligent Systems in Accounting, Finance & Management 9(2), 67–92 (2000)CrossRefGoogle Scholar
  10. 10.
    Wohed, P., Van der Aalst, W.M.P., Dumas, M., Ter Hofstede, A., Russell, N.: On the suitability of bpmn for business process modelling. In: Dustdar, S., Fiadeiro, J.L., Sheth, A.P. (eds.) BPM 2006. LNCS, vol. 4102, pp. 161–176. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  11. 11.
    Russell, N., Van der Aalst, W.M.P., Ter Hofstede, A., Wohed, P.: On the Suitability of UML 2.0 Activity Diagrams for Business Process Modelling. In: Third Asia-Pacific Conference on Conceptual Modelling (APCCM 2006), Australia (2006)Google Scholar
  12. 12.
    Ehrig, M., Koschmider, A., Oberweis, A.: Measuring similarity between semantic business process models. In: Roddick, J.F., Hinze, A. (eds.) Proceedings of the Fourth Asia-Pacific Conference on Conceptual Modelling (APCCM 2007). Australian Computer Science Communications, vol. 67, pp. 71–80. ACM, New York (2007)Google Scholar
  13. 13.
    Karagiannis, D., Hoefferer, P.: Metamodels in action: An overview. In: Filipe, J., Shishkov, B., Helfert, M. (eds.) ICSOFT 2006 - First International Conference on Software and Data Technologies, Insticc Press, Setùbal (2006)Google Scholar
  14. 14.
    Lautenbacher, F., Bauer, B., Seitz, C.: Semantic Business Process Modeling - Benefits and Capability. In: AAAI Spring Symposium, Stanford University, California. AAAI, Menlo Park (2008)Google Scholar
  15. 15.
    Hoefferer, P.: Achieving Business Process Model Interoperability Using Metamodels and Ontologies. In: Oesterle, H., Schelp, J., Winter, R. (eds.) Proceedings of the 15th European Conference on Information Systems (ECIS 2007), pp. 1620–1631. University of St. Gallen, St. Gallen (2007)Google Scholar
  16. 16.
    Hepp, M., Leymann, F., Domingue, J., Wahler, A., Fensel, D.: Semantic business process management: a vision towards using semantic web services for business process management. In: IEEE International Conference on e-Business Engineering, 2005. ICEBE 2005, pp. 535–540 (2005)Google Scholar
  17. 17.
    Fill, H.G.: Design of Semantic Information Systems using a Model-based Approach. In: AAAI Spring Symposium, Stanford University, CA. AAAI, Menlo Park (2009)Google Scholar
  18. 18.
    Stein, S., Stamber, C., El Kharbili, M., Rubach, P.: Semantic Business Process Management: An Empirical Case Study. In: Loos, P., Nuettgens, M., Turowski, K., Werth, D. (eds.) MobIS Workshops, vol. 420, pp. 165–177 (2008)Google Scholar
  19. 19.
    Heerspink, H., Dobre, D., Hillege, H., Grobbee, D., De Zeeuw, D.: Does the European Clinical Trials Directive really improve clinical trial approval time? British Journal of Clinical Pharmacology 66(4), 546–550 (2008)CrossRefGoogle Scholar
  20. 20.
    Canary Ltd.: Voluntary harmonisation procedure pilot begins. CRAdvisor - A newsletter for those involved in clinical trials (236) (2009)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Hans-Georg Fill
    • 1
  • Ilona Reischl
    • 2
  1. 1.University of ViennaViennaAustria
  2. 2.AGES PharmMedViennaAustria

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