Presentation given by Prof Fernando J Martin-Sanchez at the HISA (Health Informatics Society Australia) event "A Leap into E-Health" - see http://www.hisa.org.au/events/event_details.asp?id=211738 for further details - on 29th February 2012.

1. “(Health) (Clinical)
(Medical) (Translational),…
Bioinformatics”
HISA Victoria – A leap into eHealth
29 Feb 2012
Fernando J. Martin-Sanchez
Professor and Chair of Health Informatics
Melbourne Medical School
&
Director, Health and Biomedical Informatics Research (HBIR) Unit
Faculty of Medicine, Dentistry & Health Sciences

2. Objectives
• Terminology (What is xBioinformatics?)
• Importance (Why should we care?)
• Role of Informatics in Personalised medicine (How?)

3. Terminology
and
Definitions
(What?)

4. What is “Health and Biomedical
Informatics”

5. Different “flavours” of Health Informatics
• Medical informatics • Cancer informatics
• Nursing informatics • Cardio informatics
• Pharma informatics Profession • Neuro informatics Specialty
• Dental informatics • Pain informatics
• Pathology informatics
• …
• ...
• Public health informatics • e-health
• Clinical informatics • m-health
• Research informatics User • i-health Tech
• Consumer informatics • u-health
• ...
• …

6. AMIA endorsed framework – Based on T.
Shortliffe’s idea

7. Different scope, different methods

8. 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.

9. Importance
(Why?)

10. Current challenges in Medicine
• Need
of
earlier
diagnosis
• More
personalized
therapies
• Risk
profiling,
disease
predic8on
and
preven8on
• Improve
disease
classifica8on
systems
• Control
health
system
costs
• Clinical
trials
and
the
development
of
new
drugs
need
to
be
more
agile
and
effec8ve.
• Ci8zens
could
take
more
responsibility
for
the
maintenance
of
their
own
health.

11. Why personalised medicine?
• To develop 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

12. Advances in genomic technology
• DNA
Sequencer
–
designed
to
sequence
the
en4re
human
genome
in
a
day
for
$1,000
Benchtop
Ion
Proton™

13. 1

14. 1

15. Clinical applications of genomic information
• Pharmacogenetics - PMC
• Molecular autopsy
• Fetal DNA sequencing to preempt
amniocentesis
• Cystic fibrosis – successful clinical
trial for a specific mutation
• Identification of metabolic diseases

16. Role of
Informatics in
personalised
medicine
(How?)

17. Patient data collection
Environmental sensors Genomic sensors
Phenomic sensors
Environmental risk factors Biomarkers (DNA sequence,
(pollution, radiation, toxic agents, …) proteins, gene expression, epigenetics
Physiological, biochemical parameters
(cholesterol, temperature, glucose, heart rate…)
Integrated personal health record

18. Adapted from: Stead et al. 2011, Acad. Med.

19. The role of Biomedical Informatics to facilitate Genomic
Medicine
• Data acquisition at the point of care, including the use of
new nanodevices for diagnosis and ultra DNA sequencing
• Data integration (putting into context molecular information
from the patient with existing biomedical knowledge on the
web and integrating it with the health record)
• Supporting decision making through new clinical guidelines,
alerting systems which take into account the results of
genetic testing and pharmacogenetics approaches
• Education of patients and health professionals in genomics
and informatics
19
1

20. AMIA definition
• Translational Bioinformatics is the
development of storage, analytic, and
interpretive methods to optimize the
transformation of increasingly voluminous
biomedical data, and genomic data, into
proactive, predictive, preventive, and
participatory health.

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