Using Semantic Web Technologies for Clinical Trial Recruitment

  • Paolo Besana
  • Marc Cuggia
  • Oussama Zekri
  • Annabel Bourde
  • Anita Burgun
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6497)

Abstract

Clinical trials are fundamental for medical science: they provide the evaluation for new treatments and new diagnostic approaches. One of the most difficult parts of clinical trials is the recruitment of patients: many trials fail due to lack of participants. Recruitment is done by matching the eligibility criteria of trials to patient conditions. This is usually done manually, but both the large number of active trials and the lack of time available for matching keep the recruitment ratio low.

In this paper we present a method, entirely based on standard semantic web technologies and tool, that allows the automatic recruitment of a patient to the available clinical trials. We use a domain specific ontology to represent data from patients’ health records and we use SWRL to verify the eligibility of patients to clinical trials.

References

  1. 1.
    Allen, J.F.: An interval-based representation of temporal knowledge. In: Proceedings of the 7th IJCAI, pp. 221–226 (1981)Google Scholar
  2. 2.
    Aronson, A.R.: Effective mapping of biomedical text to the UMLS Metathesaurus: the MetaMap program. In: Proceedings of the AMIA Symposium, p. 17. American Medical Informatics Association (2001)Google Scholar
  3. 3.
    Bodenreider, O.: The unified medical language system (UMLS): integrating biomedical terminology. Nucleic Acids Research 32(database issue), D267 (2004)Google Scholar
  4. 4.
    Bodenreider I, O., Burgun, A.: Towards desiderata for an ontology of diseases for the annotation of biological datasets. In: International Conference on Biomedical Ontology 2009 (July 2009)Google Scholar
  5. 5.
    Horrocks, I., Patel-Schneider, P.F., Boley, H., Tabet, S., Grosof, B., Dean, M.: SWRL: A Semantic Web Rule Language Combining OWL and RuleML. W3C Member Submission 21 May 2004 In: World Wide Web Consortium (2004)Google Scholar
  6. 6.
    Noy, N.F., de Coronado, S., Solbrig, H., Fragoso, G., Hartel, F.W., Musen, M.A.: Representing the NCI Thesaurus in OWL DL: Modeling tools help modeling languages. Applied Ontology 3(3), 173–190 (2008)Google Scholar
  7. 7.
    Shankar, R.D., Martins, S.B., O’Connor, M.J., Parrish, D.B., Das, A.K.: Epoch: an ontological framework to support clinical trials management. In: Proceedings of the International Workshop on Healthcare Information and Knowledge Management, p. 32. ACM, New York (2006)Google Scholar
  8. 8.
    Sioutos, N., Coronado, S., Haber, M.W., Hartel, F.W., Shaiu, W.L., Wright, L.W.: NCI Thesaurus: a semantic model integrating cancer-related clinical and molecular information. Journal of biomedical informatics 40(1), 30–43 (2007)CrossRefGoogle Scholar
  9. 9.
    Srinivas, K., Patel, C., Cimino, J., Ma, L., Dolby, J., Fokoue, A., Kalyanpur, A., Kershenbaum, A., Schonberg, E.: Matching patient records to clinical trials using ontologies. In: Aberer, K., Choi, K.-S., Noy, N., Allemang, D., Lee, K.-I., Nixon, L.J.B., Golbeck, J., Mika, P., Maynard, D., Mizoguchi, R., Schreiber, G., Cudré-Mauroux, P. (eds.) ASWC 2007 and ISWC 2007. LNCS, vol. 4825, pp. 809–822. Springer, Heidelberg (2007)Google Scholar
  10. 10.
    Weng, C., Tu, S.W., Sim, I., Richesson, R.: Methodological Review: Formal representation of eligibility criteria: A literature review. Journal of Biomedical Informatics 43(3), 451–467 (2010)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Paolo Besana
    • 1
  • Marc Cuggia
    • 1
  • Oussama Zekri
    • 2
  • Annabel Bourde
    • 1
  • Anita Burgun
    • 1
  1. 1.Université de Rennes 1France
  2. 2.Centre Eugéne MarquisFrance

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