ICT for a Global Infrastructure for Health Research

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ICT for a Global Infrastructure for Health Research. Martin-Sanchez F. eHealth week 2010 (Barcelona: CCIB Convention Centre; 2010)

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ICT for a Global Infrastructure for Health Research

  1. 1. ICT for a Global Infrastructure for Health Research Dr. Fernando Martin-Sanchez Director, Medical NanoBioInformatics Dept. Institute of Health “Carlos III” Madrid, Spain
  2. 2. Objectives of the session • Background - Biomedical research is an information intensive activity - There exist new avenues in biomedical research - New data types (extremely complex and heterogeneous)are being generated at an unprecedented pace • Main issues - How can we collect, store, integrate and process this information - high throughput - distributed computing? - How can we use research data to model and simulate human physiology and pathology? - How can we promote the use of the EHR for research?
  3. 3. Participants Dr. Fernando Martin-Sanchez. Instituto de Salud Carlos III. Prof. Vicente Hernandez Universitat Politécnica de Valencia Prof. Alex Frangi, University Pompeu Fabra, Barcelona Dr. Octavian Purcarea, Chief Research and Strategy Officer. Microsoft
  4. 4. Background • New trends in medicine • Data collection - The “Nanoscope” - High-throughput sequencing - High-throughput phenotyping • Data integration • Data analysis and decision support
  5. 5. Genomic medicine
  6. 6. Why personalised medicine? • To develope individualized treatment regimes to avoid failures, inefficiency and adverse reactions related to drug therapy • To facilitate early diagnosis and advance in risk profiling, disease prediction and prevention • To improve disease classification systems • Growing health system costs
  7. 7. Why now? • Advances in Information Technologies • Results from the Human Genome Project and the Human Genetic Variation Map (Hapmap) • Laboratory technologies for personal genome sequencing • Growing knowledge about molecular causes of disease
  8. 8. EC support to personalised medicine (2001-)
  9. 9. New trends in medicine • Genomic (molecular, personalised) medicine • Regenerative medicine/tissue engineering seeks to develop functional cell, tissue, and organ substitutes to repair, replace or enhance biological function that has been lost due to congenital abnormalities, injury, disease, or aging (NIH Definition, NIBIB, June 2004) • NanoMedicine – Use of nanoscale tools and components for the diagnosis, prevention and treatment of diseases and for understanding their pathophysiology (European Science Foundation, Nov. 2005)
  10. 10. Why nano and regenerative medicine? • Cellular function takes place at the Nano level: molecular nano-machines • There are several nano-objects that can produce disease (LDL, viruses, pollutans) • The cause of the disease can be “nano” but treatment is now “micro” or “macro” • Advances in tissue engineering, cell and gene therapy
  11. 11. ActionGrid - EC project • ACTION-Grid is an international cooperative support action on - Medical Informatics - Bioinformatics - Grid Computing - Nanoinformatics • from Jun 08 to Jun 10 • Coordination. Prof. Victor Maojo - UPM
  12. 12. Data collection F. Martin-Sanchez. “New Technologies and Applications Towards Genomic Medicine”. En XIX Image Analysis Course of the Univ. La Laguna, Personalized virtual medicine (p-Health) 6th-19th March 2006. CATAI: 2006, 68-73 pp.
  13. 13. Data collection: The “Nanoscope” i.e.: i.e.: DNA Transdermal ultrasequencers glucose monitoring i.e.: Nanosensors for Radiation, contamination, Toxicity) Martín-Sanchez et al. “A primer in knowledge management for Nanoinformatics in Medicine”. IOS-Press Proceedings 12th International Conference on Knowledge-Based Intelligent Information & Engineering Systems KES2008.
  14. 14. Information processing in Nanomedicine - Nanoinformatics http://www.nanotech.neu.edu/medicine/ Maojo, Martín-Sanchez et al. “”Nanoinformatics and DNA computing: catalizing nanomedicine”. (2010) Pediatric Research. Special issue on Nanomedicine.
  15. 15. High-throughput sequencing Fred Sanger 15 September 2005 Volume 437 Number 7057 pp376-380
  16. 16. Human genomes sequenced up to now • James Watson, 454. $70 mill • Craig Venter, Sanger, - $1 mill. • African - HapMap – Illumina & Solid, $100.000 • Five african – Penn State Univ. • Chinese, Illumina • Two koreans • Prof. Quake - Stanford - - Nature genetics paper - $50.000, 1 week, Helicos SMS . Stanford team - Clinical annotation of genome from “patient Zero” • Drug metabolism • Rare genetic variants - rare diseases • Common genetic variants - Risk of complex diseases
  17. 17. High throughput phenotyping • Disease specific algorithms scanning across electronic medical records - generate structured ,standardized, anonymized, clinical data sets for research • Important issues: • NLP on administrative, laboratory and medical data • Reproducibility and standardisation • Privacy and confidenciality
  18. 18. Data integration • Ontologies • NCBO Bioportal • 168 ontologies: from Nanomedicine to public health • Browser, mappings, visualization features • Useful for annotation of data resources
  19. 19. Data analysis: GWAS (Genome Wide Association Studies) • >500.000 SNPs, >2000 individuals • Connecting molecular data with clinical phenotypes through system biology approaches: - genetic networks - pathway analysis - interaction maps • Analysis methods - Bayesian networks,Markov graphs, Petri nets...
  20. 20. The central role of EHR
  21. 21. From data collection to medical decision making
  22. 22. Final remark: from particle to population Altman RB, Balling R, Brinkley JF, Coiera E, Consorti F, Dhansay MA, Geissbuhler A, Hersh W, Kwankam SY, Lorenzi NM, Martin-Sanchez F, Mihalas GI, Shahar Y, Takabayashi K, Wiederhold G. "Commentaries on Informatics and medicine: from molecules to populations". Methods Inf Med. 2008;47(4):296-317. PMID: 18690363

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