In June this year, Prof Martin-Sanchez traveled to Heidelberg, Germany to represent HBIR and University of Melbourne participating in a three day scientific symposium "Biomedical Informatics: Confluence of Multiple Disciplines”. These are the slides from the presentation he gave to the symposium.

1. Interdisciplinarity and complexity as
opportunities for research innovation in
Health and Biomedical Informatics
50 years MIM Symposium – 10 June 2011
Fernando J. Martin-Sanchez
Professor and Chair of Health Informatics
Melbourne Medical School
Faculty of Medicine, Dentistry & Health Sciences
&
Director, Centre for Health and Biomedical Informatics Research
(CeHBIR)

2. Health & Biomedical Informatics
Challenges
• Medicineincreasingly relies on advances
in other scientific and technological
disciplines (Physics, Chemistry, Biology,
Engineering, Nanotechnology..)
• Thereare trends in biomedical research
that pose new challenges in terms of
information processing
• Newdata types (extremely complex and
heterogeneous) are being generated at
an unprecedented pace

3. 3

4. New trends in Medicine
• Genomic (molecular, personalized) 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

5. Partnership

6. • In this context, highly multidisciplinary and complex, one
could feel easily overwhelmed or might consider it as an
opportunity for research innovation in HBI.

8. Complexity

9. A Definition of Complexity
“Complexity is that property of a model
which makes it difficult to formulate its
overall behaviour in a given language,
even when there is reasonably
complete information about its atomic
components and their inter-relations”.
Bruce Edmonds, Univ. of Manchester , 1999

10. Complexity
• These factors are having another very important effect,
consisting of a very sharp increase of complexity:
– available knowledge about diseases, diagnostic and
therapeutic procedures,
– the environment in which we work (health care levels,
jurisdictions, management models),
– multiple stressing forces (aging population, increasing
number of chronic patients, sustainability of the system,
legal regulation).
• All these elements are also reflected in the complexity of the
information space in which we have to carry out our work as
well as in the systems that we have to design and develop.

11. Negative aspects

12. It can be reduced

13. People get used to complexity – It can work

14. But complexity is a Science
http://upload.wikimedia.org/wikipedia/en/a/ad/Complexity-map_castellani.jpg

15. Pathways and regulatory networks in biology

16. Complex diseases, environmental and genetic
risk factors
Ashley et al. The
Lancet, Volume
375, Issue 9725,
Pages 1525 - 1535,
1 May 2010

17. Clinical utility gene cards

18. From GWAS to EWAS
Environment-Wide
Association Study
on Type 2
Diabetes Mellitus
266 environmental
Factors
Future: combined
GWAS-EWAS?
Patel et al. 2010 PloS One

19. Our projects
Information retrieval - DiseaseCard Knowledge Management 2.0 - BIKMAS
Genetic–CPGs – With UPM - Infogenmed Education – Genome Game

20. Interdisciplinarity

21. Amazing news!!!

22. Disciplins in Biomedicine
• It’s not the object of study, but how we look at it.
• Physics (radiation, ultrasound, materials,
electrical signals)
• Chemistry (Molecules)
• Biology (Genes and proteins)
• Histology (Images from cells and tissue)
• Anatomy (organs and the whole body)
• Clinical Sciences (Symptoms, effect of
treatments)
• Psychology (behaviour, cognitive signs)
• Public Health (aggregated data from populations,
environmental factors)

23. “The Nanoscope”
i.e.: i.e.:
DNA Transdermal
ultrasequencers glucose level
monitoring
i.e.:
Martín-Sanchez et al. “A primer in knowledge
management for Nanoinformatics in Medicine”. IOS- Nanosensors for
Press Proceedings 12th International Conference on
Knowledge-Based Intelligent Information & Radiation, contamination,
Engineering Systems KES2008.
Toxicity)

24. Nanomedicine and regenerative medicine
• Data on patient (MI)
– (in ePHR): Data on loss of function, status of immuno-compatibility, tissue
characteristics,
– Genomic data through next generation sequencing - whole human genome.
– How to access the complete genome sequence so that it can be part of the EMR.
– Data about the family history of the donor for stem cell therapies
• Data on biomaterials (NI)
– Tissue, material or nano-particle, relevant references about the topic
– Chemical information such as molecules, or
– Physical information such as electromagnetic waves, optical information, electrical
signals, acoustic waves, mechanical information (mass, speed, acceleration…).
• Data on biological processes (BI)
– Metabolic pathways, genes, gene expression, protein structure and post-translational
changes.
– Genes, hormone and growth factors involved in disease and in regenerative process.
– Optimization of appropriate vectors for specific cell types, including stem and
progenitor cells and their use in bioengineered scaffolds and implants;

25. Interdisciplinarity
• Intradisciplinary analysis involves work within a single
discipline
• Crossdisciplinary activity views one discipline from the
perspective of another
• Multidisciplinary analysis draws on the knowledge of
several disciplines, each of which provides a different
perspective on a problem or issue. Each discipline
makes a contribution to the overall understanding of
the issue, but in a primarily additive fashion.
• Interdisciplinary analysis requires integration of
knowledge from the disciplines being brought to bear
on an issue. Disciplinary knowledge, concepts, tools,
and rules of investigation are combined in such a way
that the resulting understanding is greater than simply
the sum of its disciplinary parts.
Interdisciplinarity: An Introduction
Michael Seipel, Ph.D., Truman State University,
Kirksville, Missouri

26. Measuring interdisciplinarity
• It can be measured, mapped and compared
• 18 macro-disciplines of Science, from ISI (2007)

27. Measuring interdisciplinarity
• It can be measured, mapped and compared
Rafols, I., Porter, A.L. and Leydesdorff, L. (In press, 2010) Overlay Maps of Science:
Their Potential Usage in Science Policy and Research Management. Journal of the
American Society for Information Science and Technology.

28. The value of interdisciplinarity
• Probably the major disservice that experts provide in
confronting the problems of mankind is dividing the
problem in little pieces and parceling them out to
specialists. . . .
• Although it is undeniable that each specialty has much of
importance to say, it is very doubtful that the sum of all
these specialized utterances will ever add to a coherent
solution, because the problems are not independent and
sequential but highly interrelated and simultaneous.
• Someone has to look at the whole, even if it means
foregoing full knowledge of all of the parts.
Could this be a role for the next generation Herman Daly, Economist
of HBI scientists?

29. Biomedical Informatics: Biomedical Information
processing from particle to population
Multilevel modeling, ontologies, data integration, data
mining, …
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

30. HBI and the Convergence of technologies

31. HBI and the Convergence of technologies

32. From reductionism to integrative thinking
Molecules
Cells Physiome
Tissues Project
Organs
Systems
Biology
Physics Convergent
By discipline
Engineering
technologies
Nano
Chemistry
Medical
Informatics Biomedical
Informatics
Bioinformatics
Reduce complexity Understand systems
by subdividing … Nanoinformat. by integrating knowledge

33. Conclusions
• One of the main challenges for our discipline in the
coming years is to facilitate and promote interdisciplinary
work and convergence, but also at the same time
reducing complexity.
• Our discipline is in a privileged position to address these
challenges from their current central role in the
processing of information and knowledge management.
• This perspective can certainly affect the design of
educational programs, as well as how we define,
develop, implement and evaluate our projects.

34. Thank you for your attention!
© Copyright The University of Melbourne 2011