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Methods Inf Med 2006; 45(02): 180-185
DOI: 10.1055/s-0038-1634064
Original Article
Schattauer GmbH

Designing New Methodologies for Integrating Biomedical Information in Clinical Trials

V. Maojo
1   Biomedical Informatics Group, Universidad Politecnica de Madrid, Madrid, Spain
,
M. García-Remesal
1   Biomedical Informatics Group, Universidad Politecnica de Madrid, Madrid, Spain
,
H. Billhardt
2   AI Group, Universidad Rey Juan Carlos, Madrid, Spain
,
R. Alonso-Calvo
1   Biomedical Informatics Group, Universidad Politecnica de Madrid, Madrid, Spain
,
D. Pérez-Rey
1   Biomedical Informatics Group, Universidad Politecnica de Madrid, Madrid, Spain
,
F. Martín-Sánchez
3   Medical Bioinformatics Unit, Institute of Health Carlos III, Madrid, Spain
› Author Affiliations
Further Information

Publication History

Publication Date:
06 February 2018 (online)

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Summary

Objectives: To propose a modification to current methodologies for clinical trials, improving data collection and cost-efficiency. To describe a system to integrate distributed and heterogeneous medical and genetic databases for improving information access, retrieval and analysis of biomedical information.

Methods: Data for clinical trials can be collected from remote, distributed and heterogeneous data sources.

In this distributed scenario, we propose an ontology-based approach, with two basic operations: mapping and unification. Mapping outputs the semantic model of a virtual repository with the information model of a specific database. Unification provides a single schema for two or more previously available virtual repositories. In both processes, domain ontologies can improve other traditional approaches.

Results: Private clinical databases and public genomic and disease databases (e.g., OMIM, Prosite and others) were integrated. We successfully tested the system using thirteen databases containing clinical and biological information and biomedical vocabularies.

Conclusions: We present a domain-independent approach to biomedical database integration, used in this paper as a reference for the design of future models of clinico-genomic trials where information will be integrated, retrieved and analyzed. Such an approach to biomedical data integration has been one of the goals of the IST INFOBIOMED Network of Excellence in Biomedical Informatics, funded by the European Commission, and the new ACGT (Advanced Clinico-Genomic Trials on Cancer) project, where the authors will apply these methods to research experiments.

Keywords

Database integration - clinical trials - ontologies - biomedical informatics - genomic medicine
 

  • References

  • 1 INFOGENMED: A virtual laboratory for accessing and integrating genetic and medical information for health applications. EC Project IST-2001-39013-2002-04. European Commission: Brussels;
  • 2 Billhardt H, Crespo J, Maojo V. et al. A New Method for Unifying Heterogeneous Databases. In: Crespo J, Maojo V, Martin F. Proc of ISMDA 2001. LNCS 2199-54-61. Springer Verlag, Germany:
  • 3 Maojo V, Kulikowski CA. Bioinformatics and Medical Informatics: Collaborations on the Road to Genomic Medicine?. J Am Med Inform Assoc 2003; 10 (06) 515-22.
    CrossrefPubMedSearch in Google Scholar
  • 4 Sander C. Genomic medicine and the future of health care. Science 2000; 287 5460 1977-8.
    CrossrefPubMedSearch in Google Scholar
  • 5 Annas GJ. Rules for research on human genetic variation – lessons from Iceland. N Engl J Med 2000; 342 (24) 1830-3.
    CrossrefPubMedSearch in Google Scholar
  • 6 de Groen PC. In: Berg R. A healthy database; IBM creating a system for millions of Mayo Clinic patient files. Post-Bulletin, Rochester, MN: 2002. March 25 p 1A.
    Search in Google Scholar
  • 7 Maojo V, Martin-Sanchez F. Bioinformatics: towards new directions for public health. Methods Inf Med 2004; 43 (03) 208-14.
    Thieme ConnectPubMedSearch in Google Scholar
  • 8 Mauriac L, Debled M, MacGrogan G. When will more useful predictive factors be ready for use?. Breast 2005; 14 (06) 617-23. Epub 2005 Sep 16. Review.
    CrossrefPubMedSearch in Google Scholar
  • 9 Advanced Clinico-Genomic Trials on Cancer (ACGT). Integrated Project. DG IST. European Commission, 2006-2010
    PubMed
  • 10 Kosaka T, Tohsato Y, Date S, Matsuda H, Shimojo S. An OGSA-based integration of life-scientific resources for drug discovery. Methods Inf Med 2005; 44 (02) 257-61.
    Thieme ConnectPubMedSearch in Google Scholar
  • 11 Hernandez V, Blanquer I. The Grid as a healthcare provision tool. Methods Inf Med 2005; 44 (02) 144-8.
    Thieme ConnectPubMedSearch in Google Scholar
  • 12 Kundt G. An alternative proposal for “Mixed randomization” by Schulz and Grimes. Methods Inf Med 2005; 44 (04) 572-6.
    Thieme ConnectPubMedSearch in Google Scholar
  • 13 Sujansky W. Heterogeneous Database Integration in Biomedicine. Journal of Biomedical Informatics 2001; 34 (04) 285-98.
    CrossrefPubMedSearch in Google Scholar
  • 14 Wiederhold G. Mediators in the Architecture of Future Information Systems. IEEE Computer 1992; 25 (03) 38-49.
    CrossrefPubMedSearch in Google Scholar
  • 15 Ben Miled Z, Li N, Kellett G, Sipes B, Bukhres O. Complex Life Science Multidatabase- Queries. Proc of the IEEE 2002 90 11 Nov.
  • 16 Mork P, Shaker R, Tarczy-Hornoch P. The Multiple Roles of Ontologies in the Bio Mediator Data Integration System. Proceedings of the Data Integration in the Life Sciences Workshop, July 2005
    Search in Google Scholar
  • 17 Baker PG, Brass A, Bechhofer S, Goble C, Paton N, Stevens R. TAMBIS: Transparent Access to Multiple Bioinformatics Information Sources. An Overview. Proceedings of the Sixth Int Conf on Int Syst for Mol Biol, ISMB98, Montreal.
  • 18 Marenco L, Wang TY, Shepherd G, Miller PL, Nadkarni P. QUIS: A Framework for biomedical database federation. J Am Med Inform Assoc 2004; 11 (06) 523-34.
    CrossrefPubMedSearch in Google Scholar
  • 19 Mena E, Illarramendi A, Kashyap V, Sheth AP. OBSERVER: An approach for query processing in global information systems based on interoperation between pre-existing ontologies. Distributed and parallel databases 2000; 8 (02) 223-71.
    CrossrefPubMedSearch in Google Scholar
  • 20 Stuckenschmidt H, van Harmelen F, Fensel D, Klein M, Horrocks I. Catalogue Integration: A case study in ontology-based semantic translation. Technical Report IR-474, Computer Science Department, Vrije Universiteit Amsterdam 2000
    Search in Google Scholar
  • 21 Pérez-Rey D, Maojo V, García-Remesal M, Alonso- Calvo R, Billhardt H, Martin-Sánchez F, Sousa A. ONTOFUSION: Ontology-Based Integration of Genomic and Clinical Databases. Computers in Biology and Medicine 2006. (in press).
    Search in Google Scholar
  • 22 Alonso-Calvo R, Maojo V, Billhardt H, Martin- Sanchez F, García-Remesal M, Pérez-Rey D. An Agent- and Ontology-based System for Integrating Public Gene, Protein and Disease Databases. J Biomed Inform (submitted).
  • 23 Marks RG, Conlon M, Ruberg SJ. Paradigm shifts in clinical trials enabled by information technology. Stat Med 2001; 20 (17) (18) 2683-96.
    CrossrefPubMedSearch in Google Scholar
  • 24 Kirsch SE, Lewis FM. Using the World Wide Web in health-related intervention research. A review of controlled trials. Comput Inform Nurs 2004; 22 (01) 8-18. Review.
    CrossrefPubMedSearch in Google Scholar
  • 25 Breitfeld PP, Ullrich F, Anderson J, Crist WM. Web-based decision support for clinical trial eligibility determination in an international clinical trials network. Control Clin Trials 2003; 24 (06) 702-10.
    CrossrefPubMedSearch in Google Scholar
  • 26 McAlindon T, Formica M, Kabbara K, LaValley M, Lehmer M. Conducting clinical trials over the internet: feasibility study. BMJ 2003; 327 7413 484-7.
    CrossrefPubMedSearch in Google Scholar
  • 27 Rangel SJ, Narasimhan B, Geraghty N, Moss RL. Development of an internet-based protocol to facilitate randomized clinical trials in pediatric surgery. J Pediatr Surg 2002; 37 (07) 990-4. discussion 990-4
    CrossrefPubMedSearch in Google Scholar
  • 28 Marks R, Bristol H, Conlon M, Pepine CJ. Enhancing clinical trials on the internet: lessons from INVEST. Clin Cardiol 2001; 24 (Suppl. 11) V17-23.
    PubMedSearch in Google Scholar
  • 29 Kuchenbecker J, Dick HB, Schmitz K, Behrens- Baumann W. Use of internet technologies for data acquisition in large clinical trials. Telemed J E Health 2001; 7 (01) 73-6.
    CrossrefPubMedSearch in Google Scholar
  • 30 Brandt CA, Sun K, Charpentier P, Nadkarni PM. Integration of Web-based and PC-based clinical research databases. Methods Inf Med 2004; 43 (03) 287-95.
    Thieme ConnectPubMedSearch in Google Scholar
  • 31 Kohane IS, Altman RB. Health-information altruists – a potentially critical resource. N Engl J Med 2005; 353 (19) 2074-7.
    CrossrefPubMedSearch in Google Scholar
  • 32 Sax U, Schmidt S. Integration of genomic data in Electronic Health Records – opportunities and dilemmas. Methods Inf Med 2005; 44 (04) 546-50.
    Thieme ConnectPubMedSearch in Google Scholar
  • 33 Fayyad U, Piatetsky-Shapiro G, Smyth P. From Data Mining to Knowledge Discovery: An Overview. In: Fayyad U, Piatetsky-Shapiro G, Smyth P, Uthurusamy R. Advances in Knowledge Discovery and Data Mining. Menlo Park, California: AAAI Press/The MIT Press:; 1996: 1-34.
    Search in Google Scholar
  • 34 Gurwitz D, Lunshof JE, Altman RB. A call for the creation of personalized medicine databases. Nat Rev Drug Discov 2005. [Epub ahead of print].
    Search in Google Scholar
  • 35 Maurer W. Creative and Innovative Statistics in Clinical Research and Development. Methods Inf Med 2005; 44: 551-60.
    Thieme ConnectPubMedSearch in Google Scholar
  • 36 Genkin A, Kulikowski CA, Muchnik I. Set covering submodular maximization: An optimal algorithm for data mining in bioinformatics and medical informatics. Journal of Intelligent and Fuzzy Systems 2002; 12 (01) 5-17.
    PubMedSearch in Google Scholar
  • 37 Ohno-Machado L, Vinterbo SA, Weber G. Classification of gene expression data using fuzzy logic. Journal of Intelligent and Fuzzy Systems 2002; 12 (01) 19-24.
    PubMedSearch in Google Scholar
  • 38 Martín-Sanchez F, Maojo V, López-Campos G. Integrating genomics into health information systems. Methods Inf Med 2002; 41: 25-30.
    Thieme ConnectPubMedSearch in Google Scholar