INBIOMEDvision Workshop at MIE 2011. Ferran Sanz

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INBIOMEDvision Workshop at MIE 2011

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INBIOMEDvision Workshop at MIE 2011. Ferran Sanz

  1. 1. INBIOMEDvisionPromoting and Monitoring Biomedical Informatics in Europe Ferran Sanz Research Programme on Biomedical Informatics (GRIB) IMIM – Hospital del Mar Research Institute Universitat Pompeu Fabra Barcelona Biomedical Research Park (PRBB) Barcelona Ferran Sanz (UPF) @ MIE 2011
  2. 2. Workshop programme INBIOMEDvision • Ferran Sanz. IMIM-Hospital del Mar. Pompeu Fabra University. General introduction on INBIOMEDvision concepts and activities. • SørenBrunak. Center for Biological Sequence Analysis. Dept. of Systems Biology. Technical University of Denmark. Perspectives in Medical Informatics in the interface to genomics and systems biology. • Victoria López-Alonso. Carlos III Institute of Health (ISCIII). Madrid. Bioinformatics challenges in a personalised medicine pipeline. Ferran Sanz (UPF) @ MIE 2011
  3. 3. Bridging gaps between Bioinformatics and MI INBIOMEDvision Bioinformatics Medical informatics in biomedical research In health care & (molecular, “omics”, clinical research systems biology) (EHR) Ferran Sanz (UPF) @ MIE 2011
  4. 4. Bridging gaps between Bioinformatics and MI INBIOMEDvision HEAVY BARRIERS - MUTUAL IGNORANCE Bioinformatics Medical informatics in biomedical research In health care & (molecular, “omics”, clinical research systems biology) (EHR) Ferran Sanz (UPF) @ MIE 2011
  5. 5. Bridging gaps between Bioinformatics and MI INBIOMEDvision Translational Bioinformatics Bioinformatics Medical informatics in biomedical research In health care & (molecular, “omics”, clinical research systems biology) (EHR) Ferran Sanz (UPF) @ MIE 2011
  6. 6. Bridging gaps between Bioinformatics and MI INBIOMEDvision Translational Bioinformatics Bioinformatics Medical informatics in biomedical research In health care & (molecular, “omics”, clinical research systems biology) (EHR) Research re-use of clinical information Ferran Sanz (UPF) @ MIE 2011
  7. 7. Bridging gaps between Bioinformatics and MI INBIOMEDvision Translational Bioinformatics Bioinformatics Medical informatics in biomedical research In health care & (molecular, “omics”, clinical research systems biology) (EHR) Research re-use of clinical information Ferran Sanz (UPF) @ MIE 2011
  8. 8. Biomedical Informatics INBIOMEDvision IT and computational approaches in Biomedicine (integrative approaches) BMI deals with the integrative management and synergic exploitation of the wide and inter-related scope of information that is generated and needed in healthcare settings, biomedical research institutions and health-related industry. Ferran Sanz (UPF) @ MIE 2011
  9. 9. Integrative Biomedical Informatics in Pharmacovigilance EHR EHR Db iv EHR Db iii EHR Db ii db i Text mining (Terminology mapping) Data extraction and integration Statistical analysis Signal detection Mining of BDs and biomedical literature In silico pharmacology Systems biology Signal substantiation Ferran Sanz (UPF) @ MIE 2011
  10. 10. Workflows for chemo-bioinformatics signal substantiation Possible drug – AE relationship Drug Adverse event to be assessed Biological pathways Drug Involved metabolites proteins Similar drugs-ligands Genetic variants (SNPs) Ferran Sanz (UPF) @ MIE 2011
  11. 11. Challenges in Biomedical Informatics (1) INBIOMEDvision For the effective development of the integrative Biomedical Informatics concept, from both the scientific and applied points of view, several key challenges have to be addressed: • Synergic integration between the computational methods and technologies used in life sciences research (Bioinformatics) and the computer sciences and applications supporting healthcare and clinical research (Medical Informatics). • This integration requires a more intense interaction between the Bioinformatics and the Medical Informatics scientific communities. Ferran Sanz (UPF) @ MIE 2011
  12. 12. Challenges in Biomedical Informatics (2) INBIOMEDvision Development of effective translational approaches that facilitate a better and quicker application of: a) knowledge resulting from the basic biomedical research in the disease prevention and treatment, b) experience accumulated in the clinical practice in the basic biomedical research. This bidirectional knowledge translation includes: a) the extension of the electronic healthcare record (EHR) concept in order to incorporate and exploit new information types, such as these resulting from the “omics” technologies, which contribute to the development of a more personalized medicine. b) a more intense and automated incorporation of phenotypic information generated in the healthcare settings into “omics” and molecular research. Ferran Sanz (UPF) @ MIE 2011
  13. 13. Challenges in Biomedical Informatics (3) INBIOMEDvision • Integration and joint exploitation of heterogeneous information stored in widespread repositories and diverse formats, which requires further progress in systems interoperability, as well as the development of more effective techniques for automatic knowledge extraction, especially from documents in free-text and multi-lingual format. • This aspect implies a focus on all the aspects related to the development, adoption and dissemination of appropriate standards and ontologies. Biomedical ontologies provide essential domain knowledge to drive data integration, information retrieval, data annotation, natural-language processing and decision support. Ferran Sanz (UPF) @ MIE 2011
  14. 14. Challenges in Biomedical Informatics (4) INBIOMEDvision • Development of innovative methods for the simulation and modelling of complex biological phenomena, as well as the corresponding computational applications, able to operate on a wide range of data types, as well as diverse length dimensions and time scales. • These computational methods and tools have to show reliable predictive capabilities, demonstrating their usefulness for the biomedical scientists and the healthcare professionals. Ferran Sanz (UPF) @ MIE 2011
  15. 15. Basic characteristics INBIOMEDvision • Coordination Support Action (CSA) (it is not a standard research project, it is devoted to the organisation and execution of a series of activities to support a specific research field) • Start date: 1-Feb-2011 • End date: 31-Jan-2013 • Partners:  Universitat Pompeu Fabra (coordination) • Fundació IMIM (managing) • Danish Technical University • Erasmus University Medical Center • Universidad Politécnicade Madrid • Instituto de SaludCarlos III • University College London • +30 additional experts committed to participate Ferran Sanz (UPF) @ MIE 2011
  16. 16. General objective INBIOMEDvision To promote Biomedical Informatics by means of: • permanent monitoring of the scientific state-of-the-art and existing activities in the theme, • prospective analysis of the emerging challenges and opportunities, and • dissemination of the knowledge in the field. Ferran Sanz (UPF) @ MIE 2011
  17. 17. Think Tanks INBIOMEDvision • Re-use of Clinical Information for Research. June 24, 2011. London. • Genotype-phenotype resources. October 5, 2011. Brussels. • Translational Bioinformatics. October 18, 2011. Barcelona. Ferran Sanz (UPF) @ MIE 2011
  18. 18. Think Tank on Research Reuse of Clinical Information INBIOMEDvision Held in London on June 24, 2011. Some conclusions (I): • The issues around the re-use of clinical data for research purposes are complex; finding optimum solutions will require a multi-disciplinary approach, including IT and data security specialists, clinicians, biomedical researchers and bioethics experts among others. • The roles of patients and their carers are crucial. These people must be listened to and empowered. • Patients can be encouraged to share their data, but this must never be made compulsory, and it should always be possible for them to opt out of and/or withdraw their data from studies. • Clinicians and healthcare centres should be on their hand encouraged to share their completely anonymised or permitted to share data. • Industry – not only the pharmaceutical and biotech industries, but also the IT industry – is an important player. IT system suppliers for hospitals must be informed about research needs. Ferran Sanz (UPF) @ MIE 2011
  19. 19. Think Tank on Research Reuse of Clinical Information INBIOMEDvision Held in London on June 24, 2011. Some conclusions (II): • Hospital IT systems should be developed to include data needed in research, and should be flexible enough to allow the frequent and simple incorporation of new data types. • Provided that standardisation is seen as a priority, it may be best for standards to be allowed to evolve pragmatically rather than trying to impose too many in advance. • Health data raises issues of security, privacy and ethics beyond those of other types of data. • It is important to raise awareness about the current problems regarding IT security, information governance, and legal issues with particular regard to clinical data. • Developing and maintaining the highest possible standards for data collection is essential. • Analysis of retrospective clinical data is likely to be of great value, but this poses particular challenges, especially in the area of quality assurance. • Preventive medicine is an important priority and is becoming increasingly more so. The re-use of clinical data research can certainly be useful for research in this field. Ferran Sanz (UPF) @ MIE 2011
  20. 20. More information at ... INBIOMEDvision www.inbiomedvision.eu Ferran Sanz (UPF) @ MIE 2011
  21. 21. Workshop programme INBIOMEDvision • Ferran Sanz. IMIM-Hospital del Mar. Pompeu Fabra University. General introduction on INBIOMEDvision concepts and activities. • SørenBrunak. Center for Biological Sequence Analysis. Dept. of Systems Biology. Technical University of Denmark. Perspectives in Medical Informatics in the interface to genomics and systems biology. • Victoria López-Alonso. Carlos III Institute of Health (ISCIII). Madrid. Bioinformatics challenges in a personalised medicine pipeline. Ferran Sanz (UPF) @ MIE 2011

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